WorldWideScience

Sample records for maximum electricity demand

  1. Study of forecasting maximum demand of electric power

    Energy Technology Data Exchange (ETDEWEB)

    Yoo, B.C.; Hwang, Y.J. [Korea Energy Economics Institute, Euiwang (Korea, Republic of)

    1997-08-01

    As far as the past performances of power supply and demand in Korea is concerned, one of the striking phenomena is that there have been repeated periodic surpluses and shortages of power generation facilities. Precise assumption and prediction of power demands is the basic work in establishing a supply plan and carrying out the right policy since facilities investment of the power generation industry requires a tremendous amount of capital and a long construction period. The purpose of this study is to study a model for the inference and prediction of a more precise maximum demand under these backgrounds. The non-parametric model considered in this study, paying attention to meteorological factors such as temperature and humidity, does not have a simple proportionate relationship with the maximum power demand, but affects it through mutual complicated nonlinear interaction. I used the non-parametric inference technique by introducing meteorological effects without importing any literal assumption on the interaction of temperature and humidity preliminarily. According to the analysis result, it is found that the non-parametric model that introduces the number of tropical nights which shows the continuity of the meteorological effect has better prediction power than the linear model. The non- parametric model that considers both the number of tropical nights and the number of cooling days at the same time is a model for predicting maximum demand. 7 refs., 6 figs., 9 tabs.

  2. Maximum power demand cost

    International Nuclear Information System (INIS)

    Biondi, L.

    1998-01-01

    The charging for a service is a supplier's remuneration for the expenses incurred in providing it. There are currently two charges for electricity: consumption and maximum demand. While no problem arises about the former, the issue is more complicated for the latter and the analysis in this article tends to show that the annual charge for maximum demand arbitrarily discriminates among consumer groups, to the disadvantage of some [it

  3. Grid-tied photovoltaic and battery storage systems with Malaysian electricity tariff:A review on maximum demand shaving

    OpenAIRE

    Subramani, Gopinath; Ramachandaramurthy, Vigna K.; Padmanaban, Sanjeevikumar; Mihet-Popa, Lucian; Blaabjerg, Frede; Guerrero, Josep M.

    2017-01-01

    Under the current energy sector framework of electricity tariff in Malaysia, commercial and industrial customers are required to pay the maximum demand (MD) charge apart from the net consumption charges every month. The maximum demand charge will contribute up to 20% of the electricity bill, and will hence result in commercial and industrial customers focussing on alternative energy supply to minimize the billing cost. This paper aims to review the technical assessment methods of a grid-conne...

  4. Electricity demand in Kazakhstan

    International Nuclear Information System (INIS)

    Atakhanova, Zauresh; Howie, Peter

    2007-01-01

    Properties of electricity demand in transition economies have not been sufficiently well researched mostly due to data limitations. However, information on the properties of electricity demand is necessary for policy makers to evaluate effects of price changes on different consumers and obtain demand forecasts for capacity planning. This study estimates Kazakhstan's aggregate demand for electricity as well as electricity demand in the industrial, service, and residential sectors using regional data. Firstly, our results show that price elasticity of demand in all sectors is low. This fact suggests that there is considerable room for price increases necessary to finance generation and distribution system upgrading. Secondly, we find that income elasticity of demand in the aggregate and all sectoral models is less than unity. Of the three sectors, electricity demand in the residential sector has the lowest income elasticity. This result indicates that policy initiatives to secure affordability of electricity consumption to lower income residential consumers may be required. Finally, our forecast shows that electricity demand may grow at either 3% or 5% per year depending on rates of economic growth and government policy regarding price increases and promotion of efficiency. We find that planned supply increases would be sufficient to cover growing demand only if real electricity prices start to increase toward long-run cost-recovery levels and policy measures are implemented to maintain the current high growth of electricity efficiency

  5. Electricity demand forecasting techniques

    International Nuclear Information System (INIS)

    Gnanalingam, K.

    1994-01-01

    Electricity demand forecasting plays an important role in power generation. The two areas of data that have to be forecasted in a power system are peak demand which determines the capacity (MW) of the plant required and annual energy demand (GWH). Methods used in electricity demand forecasting include time trend analysis and econometric methods. In forecasting, identification of manpower demand, identification of key planning factors, decision on planning horizon, differentiation between prediction and projection (i.e. development of different scenarios) and choosing from different forecasting techniques are important

  6. Electricity demand in Tunisia

    International Nuclear Information System (INIS)

    Gam, Imen; Ben Rejeb, Jaleleddine

    2012-01-01

    This paper examines the global electricity demand in Tunisia as a function of gross domestic product in constant price, the degree of urbanization, the average annual temperature, and the real electricity price per Kwh. This demand will be examined employing annual data over a period spanning almost thirty one years from 1976 to 2006. A long run relationship between the variables under consideration is determined using the Vector Autoregressive Regression. The empirical results suggest that the electricity demand in Tunisia is sensitive to its past value, any changes in gross domestic product and electricity price. The electricity price effects have a negative impact on long-run electricity consumption. However, the gross domestic product and the past value of electricity consumption have a positive effect. Moreover, the causality test reveals a unidirectional relationship between price and electricity consumption. Our empirical findings are effective to policy makers to maintain the electricity consumption in Tunisia by using the appropriate strategy. - Highlights: ► This paper examined the electricity demand in Tunisia in the long-run. ► The empirical analysis revealed that in the long-run the electricity demand is affected by changes in its past value, GDP in constant price and real electricity price. ► There is a unidirectional relationship between price and electricity consumption, that is to say, that the electricity price causes the consumption. ► Those results suggest that a pricing policy can be an effective instrument to rationalize the electricity consumption in Tunisia in the long-run.

  7. Demand for electrical energy

    International Nuclear Information System (INIS)

    Bergougnoux, J.; Fouquet, D.

    1983-01-01

    The different utilizations of electric energy are reviewed in the residential and tertiary sectors, in the industry. The competitive position of electricity in regard to other fuels has been strengthned by the sudden rise in the price of oil in 1973-1974 and 1979-1980. The evolution of electricity prices depended on the steps taken to adjust the electricity generation system. The substitution of electricity applications for hydro-carbons is an essential point of energy policy. The adjustment at all times, at least cost and most reliability, of the supply of electricity to the demand for it is a major problem in the design and operation of electric systems. National demand for power at a given moment is extremely diversified. Electricity consumption presents daily and seasonal variations, and variations according to the different sectors. Forecasting power requirements is for any decision on operation or investment relating to an electrical system. Load management is desirable (prices according to the customers, optional tariffs for ''peak-day withdrawal''). To conclude, prospects for increased electricity consumption are discussed [fr

  8. Household electricity demand profiles

    DEFF Research Database (Denmark)

    Marszal, Anna Joanna; Heiselberg, Per Kvols; Larsen, Olena Kalyanova

    2016-01-01

    Highlights •A 1-min resolution household electricity load model is presented. •Model adapts a bottom-up approach with single appliance as the main building block. •Load profiles are used to analyse the flexibility potential of household appliances. •Load profiles can be applied in other domains, .......g. building energy simulations. •The demand level of houses with different number of occupants is well captured....

  9. The demand for electricity in Israel

    Energy Technology Data Exchange (ETDEWEB)

    Beenstock, M. [Department of Economics, Hebrew University of Jerusalem, Mount Scopus, 91905 Jerusalem (Israel); Goldin, E.; Nabot, D. [EG Consulting, Hameasef 11, Jerusalem (Israel)

    1999-04-01

    Quarterly data for Israel are used to compare and contrast three dynamic econometric methodologies for estimating the demand for electricity by households and industrial companies. These are the Dynamic Regression Model and two approaches to cointegration (OLS and Maximum Likelihood). Since we find evidence of seasonal unit roots in the data we also test for seasonal cointegration. We find that the scale elasticities are similar in all three approaches but the OLS price elasticities are considerably lower. Moreover, OLS suggests non-cointegration. The paper concludes by stochastically simulating the DRMs to calculate upside-risk in electricity demand. (Copyright (c) 1999 Elsevier Science B.V., Amsterdam. All rights reserved.)

  10. The demand for electricity in Israel

    International Nuclear Information System (INIS)

    Beenstock, M.; Goldin, E.; Nabot, D.

    1999-01-01

    Quarterly data for Israel are used to compare and contrast three dynamic econometric methodologies for estimating the demand for electricity by households and industrial companies. These are the Dynamic Regression Model and two approaches to cointegration (OLS and Maximum Likelihood). Since we find evidence of seasonal unit roots in the data we also test for seasonal cointegration. We find that the scale elasticities are similar in all three approaches but the OLS price elasticities are considerably lower. Moreover, OLS suggests non-cointegration. The paper concludes by stochastically simulating the DRMs to calculate upside-risk in electricity demand. (Copyright (c) 1999 Elsevier Science B.V., Amsterdam. All rights reserved.)

  11. Projecting Electricity Demand in 2050

    Energy Technology Data Exchange (ETDEWEB)

    Hostick, Donna J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Belzer, David B. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Hadley, Stanton W. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Markel, Tony [National Renewable Energy Lab. (NREL), Golden, CO (United States); Marnay, Chris [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Kintner-Meyer, Michael C. W. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2014-07-01

    This paper describes the development of end-use electricity projections and load curves that were developed for the Renewable Electricity (RE) Futures Study (hereafter RE Futures), which explored the prospect of higher percentages (30% - 90%) of total electricity generation that could be supplied by renewable sources in the United States. As input to RE Futures, two projections of electricity demand were produced representing reasonable upper and lower bounds of electricity demand out to 2050. The electric sector models used in RE Futures required underlying load profiles, so RE Futures also produced load profile data in two formats: 8760 hourly data for the year 2050 for the GridView model, and in 2-year increments for 17 time slices as input to the Regional Energy Deployment System (ReEDS) model. The process for developing demand projections and load profiles involved three steps: discussion regarding the scenario approach and general assumptions, literature reviews to determine readily available data, and development of the demand curves and load profiles.

  12. Cut Electric Bills by Controlling Demand

    Science.gov (United States)

    Grumman, David L.

    1974-01-01

    Electric bills can be reduced by lowering electric consumption and by controlling demand -- the amount of electricity used at a certain point in time. Gives tips to help reduce electric demand at peak power periods. (Author/DN)

  13. Maximum spectral demands in the near-fault region

    Science.gov (United States)

    Huang, Yin-Nan; Whittaker, Andrew S.; Luco, Nicolas

    2008-01-01

    The Next Generation Attenuation (NGA) relationships for shallow crustal earthquakes in the western United States predict a rotated geometric mean of horizontal spectral demand, termed GMRotI50, and not maximum spectral demand. Differences between strike-normal, strike-parallel, geometric-mean, and maximum spectral demands in the near-fault region are investigated using 147 pairs of records selected from the NGA strong motion database. The selected records are for earthquakes with moment magnitude greater than 6.5 and for closest site-to-fault distance less than 15 km. Ratios of maximum spectral demand to NGA-predicted GMRotI50 for each pair of ground motions are presented. The ratio shows a clear dependence on period and the Somerville directivity parameters. Maximum demands can substantially exceed NGA-predicted GMRotI50 demands in the near-fault region, which has significant implications for seismic design, seismic performance assessment, and the next-generation seismic design maps. Strike-normal spectral demands are a significantly unconservative surrogate for maximum spectral demands for closest distance greater than 3 to 5 km. Scale factors that transform NGA-predicted GMRotI50 to a maximum spectral demand in the near-fault region are proposed.

  14. Residential electricity demand in Singapore

    International Nuclear Information System (INIS)

    Ang, B.W.; Goh, T.N.; Liu, X.Q.

    1992-01-01

    Residential electricity consumption in Singapore increased at a rate of 8.8% per year between 1972 and 1990. Estimates of the long-run income and price elasticities are 1.0 and -0.35, respectively. The energy-conservation campaigns that have been launched are found to have marginal effects on consumption. A statistical analysis shows that the consumption is sensitive to small changes in climatic variables, particularly the temperature, which is closely linked to the growing diffusion of electric appliances for environmental controls. There has been a temporal increase in the ownership levels of appliances associated with increasing household incomes. However, other factors were involved since the ownership levels would also increase over time after the elimination of the income effect. A large part of the future growth in electricity demand will arise from the growing need for air-conditioning, which will lead to increasingly large seasonal variations in electricity use. (author)

  15. P. Electricity demand, substitution and resources

    International Nuclear Information System (INIS)

    1976-01-01

    This report discusses the demand for electricity in New Zealand, the accuracy of demand predictions, and whether some other form of energy could be substituted for electricity. It then discusses past and possible future electricity generation in New Zealand by geothermal steam and hydro power and the resources of gas and coal that could be made available for electricity generation

  16. Perspective on electricity demand beyond 2010

    International Nuclear Information System (INIS)

    Appert, O.

    2000-01-01

    Electricity demand has been the fastest growing form of energy use in the OECD for several decades. Historically there have been strong links between national income (gross domestic product), prices and electricity use. If the trends of the past continue, the annual growth rate of electricity demand to 2020 could reach 2% in the OECD and over 4% in developing countries. Although electricity demand is expected to continue the trend of strong growth in the OECD and also in other regions of the world over the coming decades, there is some question in developed countries of the extent to which electricity demand will be moderated by '' saturation ''. That is, will demand growth level off as electricity completes its penetration into most potential applications and equipment becomes more energy efficient? Will commitments to reduce emissions of conventional airborne pollutants and carbon dioxide increase the cost of electricity generation and slow electricity's demand growth? Or, working in the opposite direction, will new end-uses continue to drive electricity's increasing share of final energy consumption? Will lower prices due to electricity market reform have an impact? This paper explores these issues and provides insights in the likely trends in these areas. (author)

  17. Pay for load demand - electricity pricing with load demand component

    International Nuclear Information System (INIS)

    Pyrko, Jurek; Sernhed, Kerstin; Abaravicius, Juozas

    2003-01-01

    This publication is part of a project called Direct and Indirect Load Control in Buildings. Peak load problems have attracted considerable attention in Sweden during last three winters, caused by a significant decrease in available reserve power, which is a consequence of political decisions and liberalisation of the electricity market. A possible way to lower peak loads, avoiding electricity shortages and reducing electricity costs both for users and utilities, is to make customers experience the price difference during peak load periods and, in this way, become more aware of their energy consumption pattern and load demand. As of January 1st 2001, one of the Swedish energy utilities - Sollentuna Energi - operating in the Stockholm area, introduced a new electricity tariff with differentiated grid fees based on a mean value of the peak load every month. This tariff was introduced for all residential customers in the service area. The objective of this study is to investigate the extent to which a Load Demand Component, included in electricity pricing, can influence energy use and load demand in residential buildings. What are the benefits and disadvantages for customers and utilities? This paper investigates the impact of the new tariff on the utility and different types of typical residential customers, making comparisons with previous tariff. Keywords Load demand, electricity pricing, tariff, residential customers, energy behaviour

  18. Energy demand of electricity generation

    International Nuclear Information System (INIS)

    Drahny, M.

    1992-01-01

    The complex energy balance method was applied to selected electricity generation subsystems. The hydroelectric, brown coal based, and nuclear based subsystems are defined. The complex energy balance basically consists in identifying the mainstream and side-stream energy inputs and outputs for both the individual components and the entire electricity generation subsystem considered. Relationships for the complete energy balance calculation for the i-th component of the subsystem are given, and its side-stream energy inputs and outputs are defined. (J.B.). 4 figs., 4 refs

  19. Option value of electricity demand response

    Energy Technology Data Exchange (ETDEWEB)

    Sezgen, Osman; Goldman, C.A. [Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley CA 94720 (United States); Krishnarao, P. [Citigroup Energy Inc., 1301 Fannin St, Houston, TX 77002 (United States)

    2007-02-15

    As electricity markets deregulate and energy tariffs increasingly expose customers to commodity price volatility, it is difficult for energy consumers to assess the economic value of investments in technologies that manage electricity demand in response to changing energy prices. The key uncertainties in evaluating the economics of demand-response technologies are the level and volatility of future wholesale energy prices. In this paper, we demonstrate that financial engineering methodologies originally developed for pricing equity and commodity derivatives (e.g., futures, swaps, options) can be used to estimate the value of demand-response technologies. We adapt models used to value energy options and assets to value three common demand-response strategies: load curtailment, load shifting or displacement, and short-term fuel substitution-specifically, distributed generation. These option models represent an improvement to traditional discounted cash flow methods for assessing the relative merits of demand-side technology investments in restructured electricity markets. (author)

  20. Option value of electricity demand response

    International Nuclear Information System (INIS)

    Sezgen, Osman; Goldman, C.A.; Krishnarao, P.

    2007-01-01

    As electricity markets deregulate and energy tariffs increasingly expose customers to commodity price volatility, it is difficult for energy consumers to assess the economic value of investments in technologies that manage electricity demand in response to changing energy prices. The key uncertainties in evaluating the economics of demand-response technologies are the level and volatility of future wholesale energy prices. In this paper, we demonstrate that financial engineering methodologies originally developed for pricing equity and commodity derivatives (e.g., futures, swaps, options) can be used to estimate the value of demand-response technologies. We adapt models used to value energy options and assets to value three common demand-response strategies: load curtailment, load shifting or displacement, and short-term fuel substitution-specifically, distributed generation. These option models represent an improvement to traditional discounted cash flow methods for assessing the relative merits of demand-side technology investments in restructured electricity markets. (author)

  1. Hawaiian Electric Company Demand Response Roadmap Project

    Energy Technology Data Exchange (ETDEWEB)

    Levy, Roger [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Kiliccote, Sila [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2013-01-12

    The objective of this project was to develop a “roadmap” to guide the Hawaiian Electric Company (HECO) demand response (DR) planning and implementation in support of the Hawaii Clean Energy Initiative (HCEI) 70% clean energy goal by 2030.

  2. Forecasting residential electricity demand in provincial China.

    Science.gov (United States)

    Liao, Hua; Liu, Yanan; Gao, Yixuan; Hao, Yu; Ma, Xiao-Wei; Wang, Kan

    2017-03-01

    In China, more than 80% electricity comes from coal which dominates the CO2 emissions. Residential electricity demand forecasting plays a significant role in electricity infrastructure planning and energy policy designing, but it is challenging to make an accurate forecast for developing countries. This paper forecasts the provincial residential electricity consumption of China in the 13th Five-Year-Plan (2016-2020) period using panel data. To overcome the limitations of widely used predication models with unreliably prior knowledge on function forms, a robust piecewise linear model in reduced form is utilized to capture the non-deterministic relationship between income and residential electricity consumption. The forecast results suggest that the growth rates of developed provinces will slow down, while the less developed will be still in fast growing. The national residential electricity demand will increase at 6.6% annually during 2016-2020, and populous provinces such as Guangdong will be the main contributors to the increments.

  3. Electricity demand savings from distributed solar photovoltaics

    International Nuclear Information System (INIS)

    Glassmire, John; Komor, Paul; Lilienthal, Peter

    2012-01-01

    Due largely to recent dramatic cost reductions, photovoltaics (PVs) are poised to make a significant contribution to electricity supply. In particular, distributed applications of PV on rooftops, brownfields, and other similar applications – hold great technical potential. In order for this potential to be realized, however, PV must be “cost-effective”—that is, it must be sufficiently financially appealing to attract large amounts of investment capital. Electricity costs for most commercial and industrial end-users come in two forms: consumption (kWh) and demand (kW). Although rates vary, for a typical larger commercial or industrial user, demand charges account for about ∼40% of total electricity costs. This paper uses a case study of PV on a large university campus to reveal that even very large PV installations will often provide very small demand reductions. As a result, it will be very difficult for PV to demonstrate cost-effectiveness for large commercial customers, even if PV costs continue to drop. If policymakers would like PV to play a significant role in electricity generation – for economic development, carbon reduction, or other reasons – then rate structures will need significant adjustment, or improved distributed storage technologies will be needed. - Highlights: ► Demand charges typically account for ∼40% of total electricity costs for larger electricity users. ► Distributed photovoltaic (PV) systems provide minimal demand charge reductions. ► As a result, PVs are not a financially viable alternative to centralized electricity. ► Electricity rate structures will need changes for PV to be a major electricity source.

  4. Quebec residential electricity demand: a microeconometric approach

    International Nuclear Information System (INIS)

    Bernard, J.T.; Bolduc, D.; Belanger, D.

    1996-01-01

    An economic analysis of Quebec residential electricity demand was studied by micro-simulation models. These structural models describe all components which lead to decisions upon durable holdings and electric appliance usage. The demand for space and water heating systems was evaluated. Recent price change in favour of energy sources other than electricity were taken into account. Price and income elasticity ratios were found to be low, as expected when estimating short term use. The role played by socio-economic variables on the choice of space-water heating systems and electricity use was also examined. Recent conversions have indicated a trend toward preference by households in favour of natural gas or oil over electricity. 18 refs., 5 tabs., 1 fig

  5. Electricity demand and supply to 2020

    International Nuclear Information System (INIS)

    Bertel, E.

    1991-01-01

    This paper will attempt to make projections of energy and electricity demand, and the possible share of nuclear generation in global supply, up to 2020. This horizon has been chosen because the long lead times prevailing in the energy sector imply long-term planning, even though the degree of uncertainty is quite large when looking several decades ahead. Electricity demand, as well as primary energy consumption, depends on many technical and economic factors, obviously including demography. Using statistical data for past decades, it is possible to quantify by econometric methods and the links between energy and electricity consumption and economic parameters. The models defined may then be used to make projections of future electricity consumption. The share of nuclear electricity in primary energy supply can be estimated by taking into account the various constraints and lead times limiting the deployment of nuclear generating capacity, and the shares of other energy sources in electricity generation in each country or region. It should be emphasized that the scenarios presented below are illustrative, and are not forecasts of future energy and electricity demand. Because of the method adopted and the assumptions made, the scenarios reflect a 'conventional wisdom'. However, they do incorporate concerns for environmental protection and improvements regarding energy efficiency. (author)

  6. Restructuring Electricity Markets when Demand is Uncertain

    DEFF Research Database (Denmark)

    Boom, Anette; Buehler, Stefan

    2006-01-01

    We examine the effects of reorganizing electricity markets on capacity investments, retail prices and welfare when demand is uncertain. We study the following market configurations: (i) integrated monopoly, (ii) integrated duopoly with wholesale trade, and (iii) separated duopoly with wholesale...... trade. Assuming that wholesale prices can react to changes in retail prices (but not vice versa), we find that generators install sufficient capacity to serve retail demand in each market configuration, thus avoiding blackouts. Furthermore, aggregate capacity levels and retail prices...

  7. Indonesia’s Electricity Demand Dynamic Modelling

    Science.gov (United States)

    Sulistio, J.; Wirabhuana, A.; Wiratama, M. G.

    2017-06-01

    Electricity Systems modelling is one of the emerging area in the Global Energy policy studies recently. System Dynamics approach and Computer Simulation has become one the common methods used in energy systems planning and evaluation in many conditions. On the other hand, Indonesia experiencing several major issues in Electricity system such as fossil fuel domination, demand - supply imbalances, distribution inefficiency, and bio-devastation. This paper aims to explain the development of System Dynamics modelling approaches and computer simulation techniques in representing and predicting electricity demand in Indonesia. In addition, this paper also described the typical characteristics and relationship of commercial business sector, industrial sector, and family / domestic sector as electricity subsystems in Indonesia. Moreover, it will be also present direct structure, behavioural, and statistical test as model validation approach and ended by conclusions.

  8. Reducing Electricity Demand Peaks by Scheduling Home Appliances Usage

    DEFF Research Database (Denmark)

    Rossello Busquet, Ana; Kardaras, Georgios; Iversen, Villy Bæk

    2011-01-01

    Nowadays there is a tendency to consume electricity during the same period of the day leading to demand peaks. Regular energy consumption habits lead to demand peaks at specific temporal intervals, because users consume power at the same time. In order to avoid demand peaks, users’ appliances...... should consume electricity in a more temporarily distributed way. A new methodology to schedule the usage of home appliances is proposed and analyzed in this paper. The main concept behind this approach is the aggregation of home appliances into priority classes and the definition of a maximum power...... consumption limit, which is not allowed to be exceeded during peak hours. The scenario simulated describes a modern household, where the electrical devices are classified in low and high priority groups. The high priority devices are always granted power in order to operate without temporal restrictions...

  9. Scenario analysis on future electricity supply and demand in Japan

    International Nuclear Information System (INIS)

    Zhang, Qi; Ishihara, Keiichi N.; Mclellan, Benjamin C.; Tezuka, Tetsuo

    2012-01-01

    Under continuing policies of CO 2 emissions reduction, it is crucial to consider scenarios for Japan to realize a safe and clean future electricity system. The development plans for nuclear power and renewable energy - particularly solar and wind power - are being reconsidered in light of the Fukushima nuclear accident. To contribute to this, in the present study, three electricity supply scenarios for 2030 are proposed according to different future nuclear power development policies, and the maximum penetration of renewable energy generation is pursued. On the other side of the equation, three electricity demand scenarios are also proposed considering potential energy saving measures. The purpose of the study is to demonstrate quantitatively the technological, economic and environmental impacts of different supply policy selections and demand assumptions on future electricity systems. The scenario analysis is conducted using an input–output hour-by-hour simulation model subject to constraints from technological, economic and environmental perspectives. The obtained installed capacity mix, power generation mix, CO 2 emissions, and generation cost of the scenarios were inter-compared and analyzed. The penetration of renewable energy generation in a future electricity system in Japan, as well as its relationship with nuclear power share was uncovered. -- Highlights: ► Scenario analysis is conducted on future electricity systems under different supply policies and demand assumptions. ► Scenario analysis is conducted using a input–output hour-by-hour simulation model for real-time demand-supply balance. ► The technological, economic and environmental impacts of supply policies and demand assumptions on future electricity systems are studied. ► The maximum penetration of renewable energy generation is pursued in the scenario analysis using the hour-by-hour simulation. ► The relationship between the penetration levels of renewable energy and nuclear power

  10. Meeting/Managing the demand for electricity

    International Nuclear Information System (INIS)

    Draper, E.L.

    1994-01-01

    In the United States, the demand for electricity is increasing, so several energy sources have to be considered. Fuel and gas are taken into account for new generating capacity. But there are still environmental concerns and costs associated with coal. It is also predicted that orders will be set for new nuclear units for the middle of the decade. (TEC). 3 figs

  11. Electricity Demand Forecasting Using a Functional State Space Model

    OpenAIRE

    Nagbe , Komi; Cugliari , Jairo; Jacques , Julien

    2018-01-01

    In the last past years the liberalization of the electricity supply, the increase variability of electric appliances and their use, and the need to respond to the electricity demand in the real time had made electricity demand forecasting a challenge. To this challenge, many solutions are being proposed. The electricity demand involves many sources such as economic activities, household need and weather sources. All this sources make hard electricity demand forecasting. To forecast the electr...

  12. Modelling and forecasting Turkish residential electricity demand

    International Nuclear Information System (INIS)

    Dilaver, Zafer; Hunt, Lester C

    2011-01-01

    This research investigates the relationship between Turkish residential electricity consumption, household total final consumption expenditure and residential electricity prices by applying the structural time series model to annual data over the period from 1960 to 2008. Household total final consumption expenditure, real energy prices and an underlying energy demand trend are found to be important drivers of Turkish residential electricity demand with the estimated short run and the long run total final consumption expenditure elasticities being 0.38 and 1.57, respectively, and the estimated short run and long run price elasticities being -0.09 and -0.38, respectively. Moreover, the estimated underlying energy demand trend, (which, as far as is known, has not been investigated before for the Turkish residential sector) should be of some benefit to Turkish decision makers in terms of energy planning. It provides information about the impact of past policies, the influence of technical progress, the impacts of changes in consumer behaviour and the effects of changes in economic structure. Furthermore, based on the estimated equation, and different forecast assumptions, it is predicted that Turkish residential electricity demand will be somewhere between 48 and 80 TWh by 2020 compared to 40 TWh in 2008. - Research highlights: → Estimated short run and long run expenditure elasticities of 0.38 and 1.57, respectively. → Estimated short run and long run price elasticities of -0.09 and -0.38, respectively. → Estimated UEDT has increasing (i.e. energy using) and decreasing (i.e. energy saving) periods. → Predicted Turkish residential electricity demand between 48 and 80 TWh in 2020.

  13. Economic Rebalancing and Electricity Demand in China

    Energy Technology Data Exchange (ETDEWEB)

    He, Gang [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Advanced Light Source (ALS); Stony Brook Univ., NY (United States); Lin, Jiang [Energy Foundation, Beijing (China); Yuan, Alexandria [Energy Foundation, Beijing (China)

    2015-11-01

    Understanding the relationship between economic growth and electricity use is essential for power systems planning. This need is particularly acute now in China, as the Chinese economy is going through a transition to a more consumption and service oriented economy. This study uses 20 years of provincial data on gross domestic product (GDP) and electricity consumption to examine the relationship between these two factors. We observe a plateauing effect of electricity consumption in the richest provinces, as the electricity demand saturates and the economy develops and moves to a more service-based economy. There is a wide range of forecasts for electricity use in 2030, ranging from 5,308 to 8,292 kWh per capita, using different estimating functions, as well as in existing studies. It is therefore critical to examine more carefully the relationship between electricity use and economic development, as China transitions to a new growth phase that is likely to be less energy and resource intensive. The results of this study suggest that policymakers and power system planners in China should seriously re-evaluate power demand projections and the need for new generation capacity to avoid over-investment that could lead to stranded generation assets.

  14. Demand response in Indian electricity market

    International Nuclear Information System (INIS)

    Siddiqui, Md Zakaria; Maere d'Aertrycke, Gauthier de; Smeers, Yves

    2012-01-01

    This paper outlines a methodology for implementing cost of service regulation in retail market for electricity in India when wholesale market is liberalised and operates through an hourly spot market. As in a developing country context political considerations make tariff levels more important than supply security, satisfying the earmarked level of demand takes a back seat. Retail market regulators are often forced by politicians to keep the retail tariff at suboptimal level. This imposes budget constraint on distribution companies to procure electricity that it requires to meet the earmarked level of demand. This is the way demand response is introduced in the system and has its impact on spot market prices. We model such a situation of not being able to serve the earmarked demand as disutility to the regulator which has to be minimised and we compute associated equilibrium. This results in systematic mechanism for cutting loads. We find that even a small cut in ability of the distribution companies to procure electricity from the spot market has profound impact on the prices in the spot market. - Highlights: ► Modelling the impact of retail tariff in different states on spot prices of electricity in India. ► Retail tariffs are usually fixed below appropriate levels by states due to political reasons. ► Due to revenue constraint distribution utility withdraws demand from spot market in peak hours. ► This adversely affects the scarcity rent of generators and subsequently future investment. ► We show possibility of strategic behaviour among state level regulators in setting retail tariff.

  15. Utility Sector Impacts of Reduced Electricity Demand

    Energy Technology Data Exchange (ETDEWEB)

    Coughlin, Katie

    2014-12-01

    This report presents a new approach to estimating the marginal utility sector impacts associated with electricity demand reductions. The method uses publicly available data and provides results in the form of time series of impact factors. The input data are taken from the Energy Information Agency's Annual Energy Outlook (AEO) projections of how the electric system might evolve in the reference case, and in a number of side cases that incorporate different effciency and other policy assumptions. The data published with the AEO are used to define quantitative relationships between demand-side electricity reductions by end use and supply-side changes to capacity by plant type, generation by fuel type and emissions of CO2, Hg, NOx and SO2. The impact factors define the change in each of these quantities per unit reduction in site electricity demand. We find that the relative variation in these impacts by end use is small, but the time variation can be significant.

  16. Electricity demand for South Korean residential sector

    International Nuclear Information System (INIS)

    Sa'ad, Suleiman

    2009-01-01

    This study estimates the electricity demand function for the residential sector of South Korea with the aim of examining the effects of improved energy efficiency, structural factors and household lifestyles on electricity consumption. In the study, time series data for the period from 1973 to 2007 is used in a structural time series model to estimate the long-term price and income elasticities and annual growth of underlying energy demand trend (UEDT) at the end of the estimation period. The result shows a long-term income elasticity of 1.33 and a long-term price elasticity of -0.27% with -0.93% as the percentage growth of UEDT at the end of the estimation period. This result suggests that, in order to encourage energy efficiency in the residential sector, the government should complement the market based pricing policies with non-market policies such as minimum energy efficiency standards and public enlightenment.

  17. Electricity demand for South Korean residential sector

    Energy Technology Data Exchange (ETDEWEB)

    Sa' ad, Suleiman [Surrey Energy Economics Centre (SEEC), Department of Economics, University of Surrey, Guildford, Surrey GU2 7XH (United Kingdom)

    2009-12-15

    This study estimates the electricity demand function for the residential sector of South Korea with the aim of examining the effects of improved energy efficiency, structural factors and household lifestyles on electricity consumption. In the study, time series data for the period from 1973 to 2007 is used in a structural time series model to estimate the long-term price and income elasticities and annual growth of underlying energy demand trend (UEDT) at the end of the estimation period. The result shows a long-term income elasticity of 1.33 and a long-term price elasticity of -0.27% with -0.93% as the percentage growth of UEDT at the end of the estimation period. This result suggests that, in order to encourage energy efficiency in the residential sector, the government should complement the market based pricing policies with non-market policies such as minimum energy efficiency standards and public enlightenment. (author)

  18. Electric demand and the antinuclear movement

    International Nuclear Information System (INIS)

    Studness, C.M.

    1984-01-01

    The author feels that, with electric demand growth of 4.5 to 5% per year expected, it will be only a matter of time before stepping-up the stream of utility capacity additions becomes an important issue. If demand grows 4.5% per year instead of 2.8% as projected by NERC, demand will be 10% higher and peak reserve margins about 12 percentage points lower than envisioned by the NERC projections after five years. By 1988 or 1989, little or no excess capacity will remain, and the utilities will be faced with adding twice as much capacity annually as now planned to avoid service deterioration. As questions about the adequacy of current utility capacity plans and concerns about service quality move toward center stage, the antinuclear movement should find it increasingly difficult to garner the broad support it now enjoys. Capacity represented by any uncompleted nuclear plants will appear increasingly beneficial, and those who do not have strong antinuclear sentiments should become increasingly hesitant about lending support to the movement. Accordingly, electric demand growth in due course can be expected to drain marginal supporters from the antinuclear movement and thereby erode the movement's vitality

  19. Demand-controlling marketing of electric utilities

    Energy Technology Data Exchange (ETDEWEB)

    Raffee, H; Fritz, W

    1980-01-01

    In situations like the shortage of energy resources the particular autonomy of the users concerning energy demand raises more and more aggravating problems for the electric utilities (EU) and, last not least, for society (i.e. the peak-load problem, threatening bottlenecks in the supply situation). Thus the requirement for a demand-controlling marketing strategy of the EU with the help of which the individual demand should be influenced in the following manner is legitimate. The article discusses the targets, strategies, and instruments of marketing performed by the EU under the aspect of their efficiency concerning demand control. The discussion leads to e.g. the following results: that a marketing strategy for the sensible, responsible, and efficent use of energy, in the long-term, serves both the interests of the users and the interests of the EU; that such a marketing programme can have the required controlling effects especially with the help of strategies like market segmentation and cooperation. The discussion makes also clear that a demand-controlling marketing strategy of the EU can hardly be realized without a considerable change within the organization of the EU on one hand and, on the other, without expanding the marketing programme toward a marketing strategy of balance.

  20. Future demand for electricity in Nigeria

    International Nuclear Information System (INIS)

    Ibitoye, F.I.; Adenikinju, A.

    2007-01-01

    Availability and reliability of electricity supplies have always been vexed issue in Nigeria. With an estimated population of 130 million people in AD 2005, Nigeria is the most populous country in Africa and belongs to the group of countries with the lowest electricity consumption per capita in the continent. Nigeria is also ranked among the poorest countries in the world. This paper examines the likely trend in the demand for electricity over the next 25 years under the assumptions that (i) there is a rapid economic development such that Nigeria transforms from low- to middle-income economy during this period, (ii) Nigeria meets the millennium development goals (MDG) in AD 2015, and (iii) the country achieves the status of an industrializing nation. For these to happen, this paper projects that electric-power generation will have to rise from the current capacity of 6500 MW to over 160 GW in AD 2030. This level of supply will be significant enough to increase the per capita electricity consumption to about 5000 kWh per capita by the year 2030. Even then, this just compares with the AD 2003 per capital consumption of some industrializing countries. Analysis of the level of investment required to meet the projected power demand indicates that annual investment cost will rise from US3.8 billion in AD 2006 to a peak of US21 billion in AD 2028. The total investment stream over the 25 year period comes to US262 billion or roughly US10 billion per annum. (author)

  1. Use of demand response in electricity markets

    DEFF Research Database (Denmark)

    Singh, Sri Niwas; Østergaard, Jacob

    2010-01-01

    Demand response (DR) can provide sufficient measure, if implemented successfully, to provide economic, secure and stable supply to the customers even under the variability of the generated output from renewable energy source such as wind and solar. However, there are several issues to be analyzed...... before DR implementation. This paper critically examines the present practices of the DR in the various electricity markets existing in the world including Europe. The prospect of DR in various market levels such as day-ahead (spot) market, hour-ahead market, real time/regulating market and ancillary...... market is analyzed. This paper also addresses the key issues and challenges in the implementation of DR in the electricity markets....

  2. Introducing a demand-based electricity distribution tariff in the residential sector: Demand response and customer perception

    International Nuclear Information System (INIS)

    Bartusch, Cajsa; Wallin, Fredrik; Odlare, Monica; Vassileva, Iana; Wester, Lars

    2011-01-01

    Increased demand response is essential to fully exploit the Swedish power system, which in turn is an absolute prerequisite for meeting political goals related to energy efficiency and climate change. Demand response programs are, nonetheless, still exceptional in the residential sector of the Swedish electricity market, one contributory factor being lack of knowledge about the extent of the potential gains. In light of these circumstances, this empirical study set out with the intention of estimating the scope of households' response to, and assessing customers' perception of, a demand-based time-of-use electricity distribution tariff. The results show that households as a whole have a fairly high opinion of the demand-based tariff and act on its intrinsic price signals by decreasing peak demand in peak periods and shifting electricity use from peak to off-peak periods. - Highlights: → Households are sympathetic to demand-based tariffs, seeing as they relate to environmental issues. → Households adjust their electricity use to the price signals of demand-based tariffs. → Demand-based tariffs lead to a shift in electricity use from peak to off-peak hours. → Demand-based tariffs lead to a decrease in maximum demand in peak periods. → Magnitude of these effects increases over time.

  3. Demand response offered by households with direct electric heating

    International Nuclear Information System (INIS)

    Kofod, C.; Togeby, M.

    2004-01-01

    The peak power balance in the Nordic power system is gradually turning to be very tight, especially in the electric area of southern Sweden and eastern Denmark. Power stations are closed and hardly any investments in new production are carried out. Demand response is considered essential when the formation of spot prices shall send the signal of needed investments in new capacity. Demand response which are based on individual preferences, and carried out automatically, can be one way to increase the volume of price elastic demand. Demand response need hourly metering for calculation and documentation of the decrease in demand, and controllability in order to meet the timing requirements. Within the EU SAVE project EFFLOCOM (2002 - 2004), a Danish demand response pilot project was established in 2003 including 25 single family homes with direct electrical heating. The system has been tested during the winter 2003/2004. The tested technologies include hourly metering, communication by GRPS as well as the Internet. GPRS is used for daily remote meter reading and automatic control of the electric heating including individual control of up to five zones. The system is designed for automatic activation when the Nord Pool hourly Elspot prices exceed preset levels. The system can also be used as regulating power. The EFFLOCOM Web Bite includes an interactive demonstrator of the system. The developed customer Web Bite is including the services: 1) Access to setting the limits for the maximum duration of interruption for up to five different control zones for two periods of the day and for three price levels. 2) Access to stop an actual interruption. 3) A report on the hourly, daily, weekly and monthly use of electricity and the saved bonus by demand response control. The report is updated daily. The goals of up to 5 kW controlled per house were fulfilled. Besides the demand response bonus the customers have also saved electricity. A customer survey did show that the

  4. Reducing electricity demand peaks by scheduling home appliances usage

    Energy Technology Data Exchange (ETDEWEB)

    Rossello-Busquet, A.; Kardaras, G.; Baek Iversen, V.; Soler, J.; Dittmann, L.

    2011-05-15

    Nowadays there is a tendency to consume electricity during the same period of the day leading to demand peaks. Regular energy consumption habits lead to demand peaks at specific temporal intervals, because users consume power at the same time. In order to avoid demand peaks, users' appliances should consume electricity in a more temporarily distributed way. A new methodology to schedule the usage of home appliances is proposed and analyzed in this paper. The main concept behind this approach is the aggregation of home appliances into priority classes and the definition of a maximum power consumption limit, which is not allowed to be exceeded during peak hours. The scenario simulated describes a modern household, where the electrical devices are classified in low and high priority groups. The high priority devices are always granted power in order to operate without temporal restrictions. On the contrary, the low priority devices have to pause their operation, when the algorithm dictates it, and resume it in the future. This can become beneficial for both energy companies and users. The electricity suppliers companies will be capable of regulating power generation during demand peaks periods. Moreover, users can be granted lower electricity bill rates for accepting delaying the operation of some of their appliances. In order to analyze this scenario, teletraffic engineering theory, which is used in evaluating the performance of telecommunication networks, is used. A reversible fair scheduling (RFS) algorithm, which was originally developed for telecommunication networks, is applied. The purpose is to analyze how a power consumption limit and priorities for home appliances will affect the demand peak and the users' everyday life. Verification of the effectiveness of the RFS algorithm is done by means of simulation and by using real data for power consumption and operation hours. The defined maximum power limit of 750 and 1000 Watt was not exceeded during

  5. Effect of demand management on regulated and deregulated electricity sectors

    International Nuclear Information System (INIS)

    Fahrioglu, Murat

    2016-01-01

    Our society derives a quantifiable benefit from electric power. In particular, forced outages or blackouts have enormous consequences on society, one of which is loss of economic surplus. The society relies on having a continuous supply of electrical energy. Some customers may willingly risk this continuous supply and participate in demand management programs for electrical power. If the power system grid is in trouble, electric utilities need to have demand relief. Customers willing to reduce their demand to help the system can receive an incentive fee for helping the utilities. Demand relief can be system wide or location specific. Sometimes it can be more effective to fix the electrical demand vs. supply imbalance from the demand side. The value of demand management contracts is greatly affected by customer location. Inclusion of locational attributes into the contract design procedure increases the effectiveness of the contracts by helping a utility get more value from its demand management programs. Independent System Operators and regulators, among others, can also benefit from effective demand management. This paper will investigate how this type of demand management contracts can help the electricity sector both in regulated and deregulated environments. - Highlights: • Demand management can help prevent forced electricity outages. • Both electric utilities and ISOs can use demand management. • Regulated and deregulated electricity sectors can benefit from demand management. • Demand management contracts can be effectively used in power system grids.

  6. Prediction on the charging demand for electric vehicles in Chengdu

    Science.gov (United States)

    yun, Cai; wanquan, Zhang; wei, You; pan, Mao

    2018-03-01

    The development of the electric vehicle charging station facilities speed directly affect the development of electric vehicle speed. And the charging demand of electric vehicles is one of the main factors influencing the electric vehicle charging facilities. The paper collected and collated car ownership in recent years, the use of elastic coefficient to predict Chengdu electric vehicle ownership, further modeling to give electric vehicle charging demand.

  7. A Panel Data Analysis of Electricity Demand in Pakistan

    OpenAIRE

    Azam Chaudhry

    2010-01-01

    This paper looks at the economy-wide demand and the firm level demand for electricity in Pakistan. The economy wide estimation of electricity demand uses panel data from 63 countries from 1998-2008, and finds that the elasticity of demand for electricity with respect to per capita income is approximately 0.69, which implies that a 1% increase in per capita income will lead to a 0.69% increase in the demand for electricity. The firm level analysis uses firm level data from the World Bank’s Ent...

  8. Demand forecasting of electricity in Indonesia with limited historical data

    Science.gov (United States)

    Dwi Kartikasari, Mujiati; Rohmad Prayogi, Arif

    2018-03-01

    Demand forecasting of electricity is an important activity for electrical agents to know the description of electricity demand in future. Prediction of demand electricity can be done using time series models. In this paper, double moving average model, Holt’s exponential smoothing model, and grey model GM(1,1) are used to predict electricity demand in Indonesia under the condition of limited historical data. The result shows that grey model GM(1,1) has the smallest value of MAE (mean absolute error), MSE (mean squared error), and MAPE (mean absolute percentage error).

  9. Econometric Modeling: An Application to the Demand for Electricity ...

    African Journals Online (AJOL)

    The empirical results show an inverse relationship between real appliance purchase price, the real per capita income and the demand for electricity. Also the rate of population growth rate as a proxy for electricity consumers appears to be insignificant. This reveals the clear fact that the demand for electricity is greater than ...

  10. Long-term water demand for electricity, industry and households

    NARCIS (Netherlands)

    Bijl, David L.; Bogaart, Patrick W.; Kram, Tom; de Vries, Bert J M; van Vuuren, Detlef P.

    2016-01-01

    Better water demand projections are needed in order to better assess water scarcity. The focus in this paper is on non-agricultural water demand, as this is the fastest-growing and least well-modelled demand component. We describe an end use-oriented model for future water demand in the electricity,

  11. The design of optimal electric power demand management contracts

    Science.gov (United States)

    Fahrioglu, Murat

    1999-11-01

    Our society derives a quantifiable benefit from electric power. In particular, forced outages or blackouts have enormous consequences on society, one of which is loss of economic surplus. Electric utilities try to provide reliable supply of electric power to their customers. Maximum customer benefit derives from minimum cost and sufficient supply availability. Customers willing to share in "availability risk" can derive further benefit by participating in controlled outage programs. Specifically, whenever utilities foresee dangerous loading patterns, there is a need for a rapid reduction in demand either system-wide or at specific locations. The utility needs to get relief in order to solve its problems quickly and efficiently. This relief can come from customers who agree to curtail their loads upon request in exchange for an incentive fee. This thesis shows how utilities can get efficient load relief while maximizing their economic benefit. This work also shows how estimated customer cost functions can be calibrated, using existing utility data, to help in designing efficient demand management contracts. In order to design such contracts, optimal mechanism design is adopted from "Game Theory" and applied to the interaction between a utility and its customers. The idea behind mechanism design is to design an incentive structure that encourages customers to sign up for the right contract and reveal their true value of power. If a utility has demand management contracts with customers at critical locations, most operational problems can be solved efficiently. This thesis illustrates how locational attributes of customers incorporated into demand management contract design can have a significant impact in solving system problems. This kind of demand management contracts can also be used by an Independent System Operator (ISO). During times of congestion a loss of economic surplus occurs. When the market is too slow or cannot help relieve congestion, demand management

  12. Estimating the maximum potential revenue for grid connected electricity storage :

    Energy Technology Data Exchange (ETDEWEB)

    Byrne, Raymond Harry; Silva Monroy, Cesar Augusto.

    2012-12-01

    The valuation of an electricity storage device is based on the expected future cash flow generated by the device. Two potential sources of income for an electricity storage system are energy arbitrage and participation in the frequency regulation market. Energy arbitrage refers to purchasing (stor- ing) energy when electricity prices are low, and selling (discharging) energy when electricity prices are high. Frequency regulation is an ancillary service geared towards maintaining system frequency, and is typically procured by the independent system operator in some type of market. This paper outlines the calculations required to estimate the maximum potential revenue from participating in these two activities. First, a mathematical model is presented for the state of charge as a function of the storage device parameters and the quantities of electricity purchased/sold as well as the quantities o ered into the regulation market. Using this mathematical model, we present a linear programming optimization approach to calculating the maximum potential revenue from an elec- tricity storage device. The calculation of the maximum potential revenue is critical in developing an upper bound on the value of storage, as a benchmark for evaluating potential trading strate- gies, and a tool for capital nance risk assessment. Then, we use historical California Independent System Operator (CAISO) data from 2010-2011 to evaluate the maximum potential revenue from the Tehachapi wind energy storage project, an American Recovery and Reinvestment Act of 2009 (ARRA) energy storage demonstration project. We investigate the maximum potential revenue from two di erent scenarios: arbitrage only and arbitrage combined with the regulation market. Our analysis shows that participation in the regulation market produces four times the revenue compared to arbitrage in the CAISO market using 2010 and 2011 data. Then we evaluate several trading strategies to illustrate how they compare to the

  13. Electricity demand forecasting using regression, scenarios and pattern analysis

    CSIR Research Space (South Africa)

    Khuluse, S

    2009-02-01

    Full Text Available The objective of the study is to forecast national electricity demand patterns for a period of twenty years: total annual consumption and understanding seasonal effects. No constraint on the supply of electricity was assumed...

  14. Price elasticity estimation of electricity demand in France

    International Nuclear Information System (INIS)

    Bourbonnais, Regis; Keppler, Jan Horst

    2013-10-01

    On request of the French Union of Electricity (UFE), the authors have carried out a series of econometric statistical tests in order to determine the price elasticity of electricity demand in France. The results obtained are all solid and realistic

  15. Industrial electricity demand for Turkey: A structural time series analysis

    International Nuclear Information System (INIS)

    Dilaver, Zafer; Hunt, Lester C.

    2011-01-01

    This research investigates the relationship between Turkish industrial electricity consumption, industrial value added and electricity prices in order to forecast future Turkish industrial electricity demand. To achieve this, an industrial electricity demand function for Turkey is estimated by applying the structural time series technique to annual data over the period 1960 to 2008. In addition to identifying the size and significance of the price and industrial value added (output) elasticities, this technique also uncovers the electricity Underlying Energy Demand Trend (UEDT) for the Turkish industrial sector and is, as far as is known, the first attempt to do this. The results suggest that output and real electricity prices and a UEDT all have an important role to play in driving Turkish industrial electricity demand. Consequently, they should all be incorporated when modelling Turkish industrial electricity demand and the estimated UEDT should arguably be considered in future energy policy decisions concerning the Turkish electricity industry. The output and price elasticities are estimated to be 0.15 and - 0.16 respectively, with an increasing (but at a decreasing rate) UEDT and based on the estimated equation, and different forecast assumptions, it is predicted that Turkish industrial electricity demand will be somewhere between 97 and 148 TWh by 2020. -- Research Highlights: → Estimated output and price elasticities of 0.15 and -0.16 respectively. → Estimated upward sloping UEDT (i.e. energy using) but at a decreasing rate. → Predicted Turkish industrial electricity demand between 97 and 148 TWh in 2020.

  16. Electric energy demand and supply prospects for California

    Science.gov (United States)

    Jones, H. G. M.

    1978-01-01

    A recent history of electricity forecasting in California is given. Dealing with forecasts and regulatory uncertainty is discussed. Graphs are presented for: (1) Los Angeles Department of Water and Power and Pacific Gas and Electric present and projected reserve margins; (2) California electricity peak demand forecast; and (3) California electricity production.

  17. ELECTRICITY DEMAND IN A NORTHERN MEXICO METROPOLITAN ECONOMY

    Directory of Open Access Journals (Sweden)

    Thomas M. Fullerton

    2014-10-01

    Full Text Available Using an error correction framework, this study analyzes the long- and short-run dynamics of electricity demand in Ciudad Juarez, a large metropolitan economy on Mexico’s northern border. Demand is decomposed into the total number of electricity accounts and electricity usage per customer, each of which is modeled separately. A two-stage least squares approach is used to estimate the per customer electricity demand equations due to the endogeneity of the average price variable. The results indicate sustained growth in population, employment, and income can be expected to exert substantial upward pressure on regional electric power demand. Furthermore, demand is found to be price-inelastic in this metropolitan area, suggesting that rate increases can help raise the revenues necessary to fund expansion of the electrical grid.

  18. The maximum contraceptive prevalence 'demand curve': guiding discussions on programmatic investments.

    Science.gov (United States)

    Weinberger, Michelle; Sonneveldt, Emily; Stover, John

    2017-12-22

    Most frameworks for family planning include both access and demand interventions. Understanding how these two are linked and when each should be prioritized is difficult. The maximum contraceptive prevalence 'demand curve' was created based on a relationship between the modern contraceptive prevalence rate (mCPR) and mean ideal number of children to allow for a quantitative assessment of the balance between access and demand interventions. The curve represents the maximum mCPR that is likely to be seen given fertility intentions and related norms and constructs that influence contraceptive use. The gap between a country's mCPR and this maximum is referred to as the 'potential use gap.' This concept can be used by countries to prioritize access investments where the gap is large, and discuss implications for future contraceptive use where the gap is small. It is also used within the FP Goals model to ensure mCPR growth from access interventions does not exceed available demand.

  19. Decomposition of electricity demand in China's industrial sector

    International Nuclear Information System (INIS)

    Steenhof, Paul A.

    2006-01-01

    In the past five years, China's demand for electricity has accelerated far beyond what central planners had forecasted, leading to supply constraints and costly brownouts throughout the country. This paper presents analysis of the effect of changes in the industrial sector on electricity demand, an important economic sector contributing to these above patterns as it consumes nearly 70% of the electricity generated in China. Using decomposition analysis, it is found that both increased industrial activity and fuel shifts helped increase industrial sector electricity demand between 1998 and 2002, the period of focus in this study, but significant increases in energy efficiency countered this

  20. A summary of demand response in electricity markets

    International Nuclear Information System (INIS)

    Albadi, M.H.; El-Saadany, E.F.

    2008-01-01

    This paper presents a summary of demand response (DR) in deregulated electricity markets. The definition and the classification of DR as well as potential benefits and associated cost components are presented. In addition, the most common indices used for DR measurement and evaluation are highlighted, and some utilities' experiences with different demand response programs are discussed. Finally, the effect of demand response in electricity prices is highlighted using a simulated case study. (author)

  1. Smart electric storage heating and potential for residential demand response

    OpenAIRE

    Darby, S

    2017-01-01

    Low-carbon transition plans for temperate and sub-polar regions typically involve some electrification of space heating. This poses challenges to electricity system operation and market design, as it increases overall demand and alters the temporal patterns of that demand. One response to the challenge is to ‘smarten’ electrical heating, enabling it to respond to network conditions by storing energy at times of plentiful supply, releasing it in response to customer demands and offering rapid-...

  2. An electricity generation planning model incorporating demand response

    International Nuclear Information System (INIS)

    Choi, Dong Gu; Thomas, Valerie M.

    2012-01-01

    Energy policies that aim to reduce carbon emissions and change the mix of electricity generation sources, such as carbon cap-and-trade systems and renewable electricity standards, can affect not only the source of electricity generation, but also the price of electricity and, consequently, demand. We develop an optimization model to determine the lowest cost investment and operation plan for the generating capacity of an electric power system. The model incorporates demand response to price change. In a case study for a U.S. state, we show the price, demand, and generation mix implications of a renewable electricity standard, and of a carbon cap-and-trade policy with and without initial free allocation of carbon allowances. This study shows that both the demand moderating effects and the generation mix changing effects of the policies can be the sources of carbon emissions reductions, and also shows that the share of the sources could differ with different policy designs. The case study provides different results when demand elasticity is excluded, underscoring the importance of incorporating demand response in the evaluation of electricity generation policies. - Highlights: ► We develop an electric power system optimization model including demand elasticity. ► Both renewable electricity and carbon cap-and-trade policies can moderate demand. ► Both policies affect the generation mix, price, and demand for electricity. ► Moderated demand can be a significant source of carbon emission reduction. ► For cap-and-trade policies, initial free allowances change outcomes significantly.

  3. Critical electric field for maximum tunability in nonlinear dielectrics

    Science.gov (United States)

    Akdogan, E. K.; Safari, A.

    2006-09-01

    The authors develop a self-consistent thermodynamic theory to compute the critical electric field at which maximum tunability is attained in a nonlinear dielectric. They then demonstrate that the stored electrostatic free energy functional has to be expanded at least up to the sixth order in electric field so as to define the critical field, and show that it depends solely on the fourth and sixth order permittivities. They discuss the deficiency of the engineering tunability metric in describing nonlinear dielectric phenomena, introduce a critical field renormalized tunability parameter, and substantiate the proposed formalism by computing the critical electric field for prototypical 0.9Pb(Mg1/3,Nb2/3)-0.1PbTiO3 and Ba(Ti0.85,Sn0.15)O3 paraelectrics.

  4. Estimation of the demand for electricity

    NARCIS (Netherlands)

    van Helden, GJ; Leeflang, PSH; Sterken, E

    The residential consumer of electricity is often faced with a price schedule, where the price per kWh differs according to the amountof electricity consumed. 1 1In this study, the relations between the price per kWh are not considered as a function of the time-of-use(TOU). The determination of TOU

  5. Identifying critical constraints for the maximum loadability of electric power systems - analysis via interior point method

    Energy Technology Data Exchange (ETDEWEB)

    Barboza, Luciano Vitoria [Sul-riograndense Federal Institute for Education, Science and Technology (IFSul), Pelotas, RS (Brazil)], E-mail: luciano@pelotas.ifsul.edu.br

    2009-07-01

    This paper presents an overview about the maximum load ability problem and aims to study the main factors that limit this load ability. Specifically this study focuses its attention on determining which electric system buses influence directly on the power demand supply. The proposed approach uses the conventional maximum load ability method modelled by an optimization problem. The solution of this model is performed using the Interior Point methodology. As consequence of this solution method, the Lagrange multipliers are used as parameters that identify the probable 'bottlenecks' in the electric power system. The study also shows the relationship between the Lagrange multipliers and the cost function in the Interior Point optimization interpreted like sensitivity parameters. In order to illustrate the proposed methodology, the approach was applied to an IEEE test system and to assess its performance, a real equivalent electric system from the South- Southeast region of Brazil was simulated. (author)

  6. Bayesian Analysis of Demand Elasticity in the Italian Electricity Market

    OpenAIRE

    D'Errico, Maria; Bollino, Carlo

    2015-01-01

    The liberalization of the Italian electricity market is a decade old. Within these last ten years, the supply side has been extensively analyzed, but not the demand side. The aim of this paper is to provide a new method for estimation of the demand elasticity, based on Bayesian methods applied to the Italian electricity market. We used individual demand bids data in the day-ahead market in the Italian Power Exchange (IPEX), for 2011, in order to construct an aggregate demand function at the h...

  7. Industrial companies' demand for electricity. Evidence from a micropanel

    International Nuclear Information System (INIS)

    Bjoerner, T.B.; Togeby, M.; Jensen, H.H.

    2001-01-01

    The paper presents a micro-econometric analysis of industrial companies' demand for electricity. Previous studies on electricity consumption in the industrial sector have relied on aggregate data or cross-section observations. Here we present an econometric study on electricity demand based on a panel of 2949 Danish companies followed from 1983 to 1996. It is found that estimators of electricity demand that take account of the panel structure (fixed effect models) yield considerably lower price and production elasticities compared to estimators that do not (like cross-section models). It is also investigated how various company characteristics like size, type of industrial sub-sector and electricity intensity in production influence price and production elasticities. It appears that companies with a high electricity intensity also have a high own-price elasticity

  8. Estimating elasticity for residential electricity demand in China.

    Science.gov (United States)

    Shi, G; Zheng, X; Song, F

    2012-01-01

    Residential demand for electricity is estimated for China using a unique household level dataset. Household electricity demand is specified as a function of local electricity price, household income, and a number of social-economic variables at household level. We find that the residential demand for electricity responds rather sensitively to its own price in China, which implies that there is significant potential to use the price instrument to conserve electricity consumption. Electricity elasticities across different heterogeneous household groups (e.g., rich versus poor and rural versus urban) are also estimated. The results show that the high income group is more price elastic than the low income group, while rural families are more price elastic than urban families. These results have important policy implications for designing an increasing block tariff.

  9. U.S. electric utility demand-side management 1995

    International Nuclear Information System (INIS)

    1997-01-01

    The US Electric Utility Demand-Side Management report is prepared by the Coal and Electric Data and Renewables Division; Office of Coal, Nuclear, Electric and Alternative Fuels; Energy Information Administration (EIA); US Department of Energy. The report presents comprehensive information on electric power industry demand-side management (DSM) activities in the US at the national, regional, and utility levels. The objective of the publication is to provide industry decision makers, government policy makers, analysts, and the general public with historical data that may be used in understanding DSM as it relates to the US electric power industry. The first chapter, ''Profile: US Electric Utility Demand-Side Management'', presents a general discussion of DSM, its history, current issues, and a review of key statistics for the year. Subsequent chapters present discussions and more detailed data on energy savings, peak load reductions and costs attributable to DSM. 9 figs., 24 tabs

  10. Demand Response Within Current Electricity Wholesale Market Design

    OpenAIRE

    Ramos Gutierrez, Ariana Isabel; De Jonghe, Cedric; Six, Daan; Belmans, Ronnie

    2013-01-01

    The introduction of intermittent energy resources calls for the ability to modulate consumption patterns according to electricity availability. This paper provides a brief overview of the main electricity market design characteristics and places demand response within the framework of the existing timeline of market operation. The main differences between electricity markets lie in the price formation mechanisms where some markets pay-as- cleared and some pay- as- bid for the electricity tran...

  11. Elasticities of electricity demand in urban Indian households

    International Nuclear Information System (INIS)

    Filippini, Massimo; Pachauri, Shonali

    2004-01-01

    In the past, several electricity demand studies have been published for India based on aggregate macro data at the country or sub-national/state level. Since the underlying theory of consumer demand is based on the behaviour of individual agents, the use of micro data, which reflects individual and household behaviour, more closely, can shed greater light on the nature of consumer responses. In this paper, seasonal price and income elasticities of electricity demand in the residential sector of all urban areas of India are estimated for the first time using disaggregate level survey data for about 30,000 households. Three electricity demand functions have been econometrically estimated using monthly data for the winter, monsoon and summer season in order to understand the extent to which factors like income, prices, household size and other household specific characteristics, influence variations observed in individual households' electricity demand. The results show electricity demand is income and price inelastic in all three seasons, and that household, demographic and geographical variables are significant in determining electricity demand

  12. Electricity supply and demand analysis in electric system of Uruguay 2000-2007 period

    International Nuclear Information System (INIS)

    2008-01-01

    This article is about the following topics: energy analysis, production and use, supply and demand, energy consumption evolution, energy sources, energy demand by economic sector between years 2000-2007, energy range, energy growing rate, demanding maximum power, growing maximum rate, exported and imported energy.

  13. Application of the maximum entropy production principle to electrical systems

    International Nuclear Information System (INIS)

    Christen, Thomas

    2006-01-01

    For a simple class of electrical systems, the principle of the maximum entropy production rate (MaxEP) is discussed. First, we compare the MaxEP principle and the principle of the minimum entropy production rate and illustrate the superiority of the MaxEP principle for the example of two parallel constant resistors. Secondly, we show that the Steenbeck principle for the electric arc as well as the ohmic contact behaviour of space-charge limited conductors follow from the MaxEP principle. In line with work by Dewar, the investigations seem to suggest that the MaxEP principle can also be applied to systems far from equilibrium, provided appropriate information is available that enters the constraints of the optimization problem. Finally, we apply the MaxEP principle to a mesoscopic system and show that the universal conductance quantum, e 2 /h, of a one-dimensional ballistic conductor can be estimated

  14. Demand side management of electric car charging

    DEFF Research Database (Denmark)

    Finn, P.; Fitzpatrick, C.; Connolly, David

    2012-01-01

    the purchase of alternative energy vehicles in an effort to achieve 10% EV (electric vehicle) penetration in the country's road fleet by 2020. The replacement of ICE (internal combustion engine) vehicles with EV equivalents poses challenges for grid operators while simultaneously offering opportunities...

  15. Research on electricity market operation mechanism and its benefit of demand side participation

    Science.gov (United States)

    Han, Shuai; Yan, Xu; Qin, Li-juan; Lin, Xi-qiao; Zeng, Bo

    2017-08-01

    Demand response plays an important role in maintaining the economic stability of the system, and has the characteristics of high efficiency, low cost, fast response, good environmental benefits and so on. Demand side resource is an important part of electricity market. The research of demand side resources in our country is still in the initial stage, but the opening of the electricity sales side provides a broad prospect for the development of electricity market. This paper summarizes the main types of demand side resources in our country, analyzes the economic principle of demand response from the micro perspective, puts forward some suggestions on the operation mechanism of China’s demand side resources participating in the electricity market under the condition of electricity sales side opening, analyzes the current situation of pricing in the electricity wholesale market and sets up the pricing strategy of the centralized wholesale market with the demand side power supply participating in quotation, which makes the social and economic benefits reach the maximum.

  16. Estimation of electricity demand of Iran using two heuristic algorithms

    International Nuclear Information System (INIS)

    Amjadi, M.H.; Nezamabadi-pour, H.; Farsangi, M.M.

    2010-01-01

    This paper deals with estimation of electricity demand of Iran based on economic indicators using Particle Swarm Optimization (PSO) Algorithm. The estimation is based on Gross Domestic Product (GDP), population, number of customers and average price electricity by developing two different estimation models: a linear model and a non-linear model. The proposed models are obtained based upon available actual data of 21 years; since 1980-2000. Then the models obtained are used to estimate the electricity demand of the target years; for a period of time e.g. 2001-2006 and the results obtained are compared with the actual demand during this period. Furthermore, to validate the results obtained by PSO, genetic algorithm (GA) is applied to solve the problem. The results show that the PSO is a useful optimization tool for solving the problem using two developed models and can be used as an alternative solution to estimate the future electricity demand.

  17. Electrical Assessment, Capacity, and Demand Study for Fort Wainwright, Alaska

    National Research Council Canada - National Science Library

    Vavrin, John L; Brown, III, William T; Kemme, Michael R; Allen, Marcus A; Percle, Wayne J; Loran, Robert T; Stauffer, David B; Hudson, Kenneth

    2007-01-01

    .... Of particular importance was that FWA management projected that the installation might experience electrical power shortages during the impending winter of 2006/2007 due to increases in energy demand...

  18. Dynamics of Electricity Demand in Lesotho: A Kalman Filter Approach

    Directory of Open Access Journals (Sweden)

    Thamae Retselisitsoe Isaiah

    2015-04-01

    Full Text Available This study provides an empirical analysis of the time-varying price and income elasticities of electricity demand in Lesotho for the period 1995-2012 using the Kalman filter approach. The results reveal that economic growth has been one of the main drivers of electricity consumption in Lesotho while electricity prices are found to play a less significant role since they are monopoly-driven and relatively low when compared to international standards. These findings imply that increases in electricity prices in Lesotho might not have a significant impact on consumption in the short-run. However, if the real electricity prices become too high over time, consumers might change their behavior and sensitivity to price and hence, energy policymakers will need to reconsider their impact in the long-run. Furthermore, several exogenous shocks seem to have affected the sensitivity of electricity demand during the period prior to regulation, which made individuals, businesses and agencies to be more sensitive to electricity costs. On the other hand, the period after regulation has been characterized by more stable and declining sensitivity of electricity demand. Therefore, factors such as regulation and changes in the country’s economic activities appear to have affected both price and income elasticities of electricity demand in Lesotho.

  19. Electrical power distribution control methods, electrical energy demand monitoring methods, and power management devices

    Science.gov (United States)

    Chassin, David P [Pasco, WA; Donnelly, Matthew K [Kennewick, WA; Dagle, Jeffery E [Richland, WA

    2011-12-06

    Electrical power distribution control methods, electrical energy demand monitoring methods, and power management devices are described. In one aspect, an electrical power distribution control method includes providing electrical energy from an electrical power distribution system, applying the electrical energy to a load, providing a plurality of different values for a threshold at a plurality of moments in time and corresponding to an electrical characteristic of the electrical energy, and adjusting an amount of the electrical energy applied to the load responsive to an electrical characteristic of the electrical energy triggering one of the values of the threshold at the respective moment in time.

  20. Estimation of Iranian price elasticities of residential electricity demand

    Directory of Open Access Journals (Sweden)

    Yeganeh Mousavi Jahromi

    2014-06-01

    Full Text Available This paper presents a study to determine demand for electricity in city of Yazd, Iran over the period of 1998-2008. Using vector error correction model (VECM based on seasonal information, the study determines that electricity has no elasticity in short term in household expenditure. Therefore, government policy on increasing price of electricity will not influence demand. However, electricity maintains elasticity over the long-term period and an increase on price of electricity could motivate consumers to reduce their consumption by purchasing energy efficient facilities. Therefore, any governmental strategy to increase price may have positive impact on economy. The study also detects a positive and meaningful relationship between temperature and electricity consumption.

  1. The Sensitivity of Residential Electricity Demand in Indonesia

    Directory of Open Access Journals (Sweden)

    Stranti Nastiti Kusumaningrum

    2018-03-01

    Full Text Available Since 2013, the residential electricity price for High VA (Volt-Ampere households has changed due to changes in pricing policies. This paper analyzes the responsiveness of residential electricity demand to the change in electricity prices and income among two different household groups (Low VA and High VA in 2011 and 2014. Using an electricity consumption model and the Quantile Regression method, the results show that residential electricity demand is price and income inelastic. Income elasticity is lower than price elasticity. Furthermore, the effects on price elasticity also found in the Low VA group, whose rate remained stable. At the same time, evidence proves the impact of the change in pricing policy on income elasticity remains unclear. This result implies that the government has to be more careful in regulating electricity prices for the low VA group, while maintaining economic stability.DOI: 10.15408/sjie.v7i2.6048

  2. Simulation of annual electric lighting demand using various occupancy profiles

    DEFF Research Database (Denmark)

    Iversen, Anne; Andersen, Philip Hvidthøft Delff; Svendsen, Svend

    2013-01-01

    This paper describes an investigation of the effect on electric lighting demand of applying occupancy models of various resolution to climate-based daylight modelling. The lighting demand was evaluated for a building zone with the occupant always present, with occupancy corresponding to absence...... factors, based on an estimated annual mean occupancy, based on estimated 1-hour mean occupancy, and based on 2-min occupancy intervals. The results showed little difference in the annual electric lighting demand when the same occupancy profile was used every day, as opposed to when profiles were used...... where occupancy varied every day. Furthermore, the results showed that annual electric lighting demand was evaluated slightly conservatively when a mean absence factor was applied as opposed to using dynamic occupancy profiles....

  3. Demand Response Application forReliability Enhancement in Electricity Market

    OpenAIRE

    Romera Pérez, Javier

    2015-01-01

    The term reliability is related with the adequacy and security during operation of theelectric power system, supplying the electricity demand over time and saving thepossible contingencies because every inhabitant needs to be supplied with electricity intheir day to day. Operating the system in this way entails spending money. The first partof the project is going to be an analysis of the reliability and the economic impact of it.During the last decade, electric utilities and companies had be...

  4. Price-elastic demand in deregulated electricity markets

    Energy Technology Data Exchange (ETDEWEB)

    Siddiqui, Afzal S.

    2003-05-01

    The degree to which any deregulated market functions efficiently often depends on the ability of market agents to respond quickly to fluctuating conditions. Many restructured electricity markets, however, experience high prices caused by supply shortages and little demand-side response. We examine the implications for market operations when a risk-averse retailer's end-use consumers are allowed to perceive real-time variations in the electricity spot price. Using a market-equilibrium model, we find that price elasticity both increases the retailers revenue risk exposure and decreases the spot price. Since the latter induces the retailer to reduce forward electricity purchases, while the former has the opposite effect, the overall impact of price responsive demand on the relative magnitudes of its risk exposure and end-user price elasticity. Nevertheless, price elasticity decreases cumulative electricity consumption. By extending the analysis to allow for early settlement of demand, we find that forward stage end-user price responsiveness decreases the electricity forward price relative to the case with price-elastic demand only in real time. Moreover, we find that only if forward stage end-user demand is price elastic will the equilibrium electricity forward price be reduced.

  5. Meeting residential space heating demand with wind-generated electricity

    International Nuclear Information System (INIS)

    Hughes, Larry

    2010-01-01

    Worldwide, many electricity suppliers are faced with the challenge of trying to integrate intermittent renewables, notably wind, into their energy mix to meet the needs of those services that require a continuous supply of electricity. Solutions to intermittency include the use of rapid-response backup generation and chemical or mechanical storage of electricity. Meanwhile, in many jurisdictions with lengthy heating seasons, finding secure and preferably environmentally benign supplies of energy for space heating is also becoming a significant challenge because of volatile energy markets. Most, if not all, electricity suppliers treat these twin challenges as separate issues: supply (integrating intermittent renewables) and demand (electric space heating). However, if space heating demand can be met from an intermittent supply of electricity, then both of these issues can be addressed simultaneously. One such approach is to use off-the-shelf electric thermal storage systems. This paper examines the potential of this approach by applying the output from a 5.15 MW wind farm to the residential heating demands of detached households in the Canadian province of Prince Edward Island. The paper shows that for the heating season considered, up to 500 households could have over 95 percent of their space heating demand met from the wind farm in question. The benefits as well as the limitations of the approach are discussed in detail. (author)

  6. Demand response in experimental electricity markets

    Directory of Open Access Journals (Sweden)

    Barreda-Tarrazona, Iván

    2012-03-01

    Full Text Available We study consumers’ behavior in an experimental electricity market. Subjects make decisions concerning the quantity of electric energy they want to consume in three different pricing environments. In the baseline framework, they decide under a system of fixed prices, invariant to consumption schedule as well as to network restrictions. The other two environments correspond to dynamic pricing systems combined with incentives that aim at cutting energy consumption in a number of selected situations characterized by high network congestion. In such situations, in the first environment subjects get a bonus if they reduce their peak consumption below a certain level, while in the second one, consumers are sanctioned for consuming in peak times. From a social welfare perspective, our experimental data confirm that a dynamic system for prices is more efficient than a fixed one. Moreover, a dynamic scheme with sanctions, although less preferred by consumers, is more effective than the one with bonuses in order to reduce peak consumption. Dynamic pricing with bonuses reaches a good balance between efficiency and consumer acceptance.

    Estudiamos el comportamiento de los consumidores en un mercado de electricidad diseñado en el laboratorio. Los sujetos experimentales toman decisiones sobre la cantidad de electricidad que desean consumir en tres contextos diferentes. En el tratamiento base, los consumidores deciden bajo un sistema de precios fijos, en el que el precio es invariable tanto a la franja horaria de consumo como a las restricciones de la red. Los otros dos contextos corresponden a sistemas dinámicos de precios combinados con incentivos cuyo objetivo es la reducción del consumo en algunas situaciones seleccionadas caracterizadas por una alta congestión de la red. En estas situaciones, en el primer contexto, se bonifica la reducción del consumo en la hora punta por debajo de cierto nivel, mientras que en el segundo, los consumidores

  7. Measuring the financial impact of demand response for electricity retailers

    International Nuclear Information System (INIS)

    Feuerriegel, Stefan; Neumann, Dirk

    2014-01-01

    Due to the integration of intermittent resources of power generation such as wind and solar, the amount of supplied electricity will exhibit unprecedented fluctuations. Electricity retailers can partially meet the challenge of matching demand and volatile supply by shifting power demand according to the fluctuating supply side. The necessary technology infrastructure such as Advanced Metering Infrastructures for this so-called Demand Response (DR) has advanced. However, little is known about the economic dimension and further effort is strongly needed to realistically quantify the financial impact. To succeed in this goal, we derive an optimization problem that minimizes procurement costs of an electricity retailer in order to control Demand Response usage. The evaluation with historic data shows that cost volatility can be reduced by 7.74%; peak costs drop by 14.35%; and expenditures of retailers can be significantly decreased by 3.52%. - Highlights: • Ex post simulation to quantify financial impacts of demand response. • Effects of Demand Response are simulated based on real-world data. • Procurement costs of an average electricity retailer decrease by 3.4%. • Retailers can cut hourly peak expenditures by 12.1%. • Cost volatility is reduced by 12.2%

  8. Reevaluation of Turkey's hydropower potential and electric energy demand

    International Nuclear Information System (INIS)

    Yueksek, Omer

    2008-01-01

    This paper deals with Turkey's hydropower potential and its long-term electric energy demand predictions. In the paper, at first, Turkey's energy sources are briefly reviewed. Then, hydropower potential is analyzed and it has been concluded that Turkey's annual economically feasible hydropower potential is about 188 TWh, nearly 47% greater than the previous estimation figures of 128 TWh. A review on previous prediction models for Turkey's long-term electric energy demand is presented. In order to predict the future demand, new increment ratio scenarios, which depend on both observed data and future predictions of population, energy consumption per capita and total energy consumption, are developed. The results of 11 prediction models are compared and analyzed. It is concluded that Turkey's annual electric energy demand predictions in 2010, 2015 and 2020 vary between 222 and 242 (average 233) TWh; 302 and 356 (average 334) TWh; and 440 and 514 (average 476) TWh, respectively. A discussion on the role of hydropower in meeting long-term demand is also included in the paper and it has been predicted that hydropower can meet 25-35% of Turkey's electric energy demand in 2020

  9. The price elasticity of electricity demand in South Australia

    International Nuclear Information System (INIS)

    Fan Shu; Hyndman, Rob J.

    2011-01-01

    In this paper, the price elasticity of electricity demand, representing the sensitivity of customer demand to the price of electricity, has been estimated for South Australia. We first undertake a review of the scholarly literature regarding electricity price elasticity for different regions and systems. Then we perform an empirical evaluation of the historic South Australian price elasticity, focussing on the relationship between price and demand quantiles at each half-hour of the day. This work attempts to determine whether there is any variation in price sensitivity with the time of day or quantile, and to estimate the form of any relationships that might exist in South Australia. - Highlights: → We review the scholarly literature on electricity own-price elasticity for different regions and systems. → We use annual log-linear econometric models of the electricity demand to estimate the historic South Australian price elasticity. → We focus on the relationship between price and demand quantiles at each half-hour of the day. → The overall price elasticity in South Australia ranges from -0.363 to -0.428.

  10. Climate change and electricity demand in Brazil: A stochastic approach

    International Nuclear Information System (INIS)

    Trotter, Ian M.; Bolkesjø, Torjus Folsland; Féres, José Gustavo; Hollanda, Lavinia

    2016-01-01

    We present a framework for incorporating weather uncertainty into electricity demand forecasting when weather patterns cannot be assumed to be stable, such as in climate change scenarios. This is done by first calibrating an econometric model for electricity demand on historical data, and subsequently applying the model to a large number of simulated weather paths, together with projections for the remaining determinants. Simulated weather paths are generated based on output from a global circulation model, using a method that preserves the trend and annual seasonality of the first and second moments, as well as the spatial and serial correlations. The application of the framework is demonstrated by creating long-term, probabilistic electricity demand forecasts for Brazil for the period 2016–2100 that incorporates weather uncertainty for three climate change scenarios. All three scenarios indicate steady growth in annual average electricity demand until reaching a peak of approximately 1071–1200 TWh in 2060, then subsequently a decline, largely reflecting the trajectory of the population projections. The weather uncertainty in all scenarios is significant, with up to 400 TWh separating the 10th and the 90th percentiles, or approximately ±17% relative to the mean. - Highlights: • Large number of realistic weather paths generated based on output from a single GCM. • Simulated weather paths used to include weather uncertainty in demand forecasting. • We present a probabilistic electricity demand forecast for Brazil 2016–2100. • Annual Brazilian electricity demand will peak around 2060 at about 1071–1200 TWh. • Significant weather uncertainty, ∼400 TWh separating the 10th and 90th percentiles.

  11. Modeling climate feedbacks to electricity demand: The case of China

    International Nuclear Information System (INIS)

    Asadoorian, Malcolm O.; Eckaus, Richard S.; Schlosser, C. Adam

    2008-01-01

    This paper is an empirical investigation of the effects of climate on the use of electricity by consumers and producers in urban and rural areas within China. It takes advantage of an unusual combination of temporal and regional data sets in order to estimate temperature, as well as price and income elasticities of electricity demand. The estimated positive temperature/electric power feedback implies a continually increasing use of energy to produce electric power which, in China, is primarily based on coal. In the absence of countervailing measures, this will contribute to increased emissions, increased atmospheric concentrations of greenhouse gases, and increases in greenhouse warming

  12. An analysis of a demand charge electricity grid tariff in the residential sector

    International Nuclear Information System (INIS)

    Stokke, A. V.; Doorman, G.L.; Ericson, T.

    2010-01-01

    This paper analyzes the demand response from residential electricity consumers to a demand charge grid tariff. The tariff charges the maximum hourly peak consumption in each of the winter months Dec, Jan, and Feb, thus giving incentives to reduce peak consumption. We use hourly electricity consumption data from 443 households, as well as data on their grid and power prices, the local temperature, wind speed, and hours of daylight. The panel data set is analyzed with a fixed effects regression model. The estimates indicate average demand reductions up to 0.37 kWh/h per household in response to the tariff. This is on average a 5% reduction, with a maximum reduction of 12% in hour 8 in Dec. The consumers did not receive any information on their continuous consumption or any reminders when the tariff was in effect. It is likely that the consumption reductions would have been even higher with more information to the consumers.

  13. The power to choose. Demand response in liberalized electricity markets

    International Nuclear Information System (INIS)

    2003-01-01

    Highly volatile electricity prices are becoming a more frequent and unwanted characteristic of modern electricity wholesale markets. But low demand elasticity, mainly the result of a lack of incentives and consumers' inability to control demand, means that consumer behaviour is not reflected in the cost of energy. This study analyses the impact of price-responsive demand and shows how pricing, policy and technology can be used to inform consumer behaviour and choice. Informed choice and market-based valuation of electricity supply will ensure liberalized markets are competitive, efficient, less volatile and able to provide long term security of supply. Significant benefits will occur even if only 5% of customers become responsive to price-incentives and information. And customers will respond to well designed programs, thereby developing a role in ensuring efficient price formulation for electricity. This study analyses the economic, efficiency and security benefits and identifies the changes in electricity tariffs and the network infrastructure needed to achieve greater demand response

  14. Electric utilities and the demand for natural gas

    Energy Technology Data Exchange (ETDEWEB)

    Uri, N D; Atkinson, S

    1976-03-01

    The scarcity of natural gas has given rise to a series of priorities of deliveries based on end use and drafted by the Federal Power Commission. The U.S. Supreme Court, on June 7, 1972, held that the Commission has jurisdiction over curtailments in the service of gas in interstate commerce to both resale and direct industrial customers. This decision reversed a Fifth Circuit Court ruling that protected direct industrial customers from curtailments. The FPC priority curtailments are classed from 1 to 9, for which electric utilities are concentrated in classes 4 to 9. As weather conditions become more severe, not only do the residential and commercial consumers demand more electrical energy, they also demand more natural gas. The result is that there is less natural gas available for electric utilities to use for generation so they change to an alternative fuel. A demand model for the short term for natural gas for electric utilities is given; primary factors involve the price of natural gas, the prices of substitute fuels, and the demand for electrical energy by the various consumer classes. (MCW)

  15. Modeling and forecasting of electrical power demands for capacity planning

    International Nuclear Information System (INIS)

    Al-Shobaki, S.; Mohsen, M.

    2007-01-01

    Jordan imports oil from neighboring countries for use in power production. As such, the cost of electricity production is high compared to oil producing countries. It is anticipated that Jordan will face major challenges in trying to meet the growing energy and electricity demands while also developing the energy sector in a way that reduces any adverse impacts on the economy, the environment and social life. This paper described the development of forecasting models to predict future generation and sales loads of electrical power in Jordan. Two models that could be used for the prediction of electrical energy demand in Amman, Jordan were developed and validated. An analysis of the data was also presented. The first model was based on the levels of energy generated by the National Electric Power Company (NEPCO) and the other was based on the levels of energy sold by the company in the same area. The models were compared and the percent error was presented. Energy demand was also forecasted across the next 60 months for both models. Results were then compared with the output of the in-house forecast model used by NEPCO to predict the levels of generated energy needed across the 60 months time period. It was concluded that the NEPCO model predicted energy demand higher than the validated generated data model by an average of 5.25 per cent. 8 refs., 5 tabs., 15 figs

  16. Modeling and forecasting of electrical power demands for capacity planning

    Energy Technology Data Exchange (ETDEWEB)

    Al-Shobaki, S. [Hashemite Univ., Zarka (Jordan). Dept. of Industrial Engineering; Mohsen, M. [Hashemite Univ., Zarka (Jordan). Dept. of Mechanical Engineering

    2007-07-01

    Jordan imports oil from neighboring countries for use in power production. As such, the cost of electricity production is high compared to oil producing countries. It is anticipated that Jordan will face major challenges in trying to meet the growing energy and electricity demands while also developing the energy sector in a way that reduces any adverse impacts on the economy, the environment and social life. This paper described the development of forecasting models to predict future generation and sales loads of electrical power in Jordan. Two models that could be used for the prediction of electrical energy demand in Amman, Jordan were developed and validated. An analysis of the data was also presented. The first model was based on the levels of energy generated by the National Electric Power Company (NEPCO) and the other was based on the levels of energy sold by the company in the same area. The models were compared and the percent error was presented. Energy demand was also forecasted across the next 60 months for both models. Results were then compared with the output of the in-house forecast model used by NEPCO to predict the levels of generated energy needed across the 60 months time period. It was concluded that the NEPCO model predicted energy demand higher than the validated generated data model by an average of 5.25 per cent. 8 refs., 5 tabs., 15 figs.

  17. Evaluation of the Electric Vehicle Impact in the Power Demand Curve in a Smart Grid Environment

    DEFF Research Database (Denmark)

    Morais, Hugo; Sousa, Tiago; Vale, Zita

    2014-01-01

    be beneficially used to address this problem; the massive use of electric vehicles, particularly of vehicle-to-grid (usually referred as gridable vehicles or V2G), becomes a very relevant issue. This paper addresses the impact of Electric Vehicles (EVs) in system operation costs and in power demand curve...... for a distribution network with large penetration of Distributed Generation (DG) units. An efficient management methodology for EVs charging and discharging is proposed, considering a multi-objective optimization problem. The main goals of the proposed methodology are: to minimize the system operation costs...... and to minimize the difference between the minimum and maximum system demand (leveling the power demand curve). The proposed methodology perform the day-ahead scheduling of distributed energy resources in a distribution network with high penetration of DG and a large number of electric vehicles. It is used a 32...

  18. Price-elastic demand in deregulated electricity markets

    OpenAIRE

    Siddiqui, Afzal S.

    2003-01-01

    The degree to which any deregulated market functions efficiently often depends on the ability of market agents to respond quickly to fluctuating conditions. Many restructured electricity markets, however, experience high prices caused by supply shortages and little demand-side response. We examine the implications for market operations when a risk-averse retailer's end-use consumers are allowed to perceive real-time variations in the electricity spot price. Using a market-equilibrium mo...

  19. Modelling residential electricity demand in the GCC countries

    International Nuclear Information System (INIS)

    Atalla, Tarek N.; Hunt, Lester C.

    2016-01-01

    This paper aims at understanding the drivers of residential electricity demand in the Gulf Cooperation Council countries by applying the structural time series model. In addition to the economic variables of GDP and real electricity prices, the model accounts for population, weather, and a stochastic underlying energy demand trend as a proxy for efficiency and human behaviour. The resulting income and price elasticities are informative for policy makers given the paucity of previous estimates for a region with particular political structures and economies subject to large shocks. In particular, the estimates allow for a sound assessment of the impact of energy-related policies suggesting that if policy makers in the region wish to curtail future residential electricity consumption they would need to improve the efficiency of appliances and increase energy using awareness of consumers, possibly by education and marketing campaigns. Moreover, even if prices were raised the impact on curbing residential electricity growth in the region is likely to be very small given the low estimated price elasticities—unless, that is, prices were raised so high that expenditure on electricity becomes such a large proportion of income that the price elasticities increase (in absolute terms). - Highlights: • Residential electricity demand for Bahrain, Kuwait, Oman, and Saudi Arabia • Estimated residential electricity demand relationships using STSM/UEDT approach • LR income and price elasticities from 0.43 to 0.71 and − 0.16 to zero respectively • Impact CDD elasticities from 0.2 to 0.7 • Estimated UEDTs suggest exogenous electricity using behaviour.

  20. Impacts of Demand-Side Resources on Electric Transmission Planning

    Energy Technology Data Exchange (ETDEWEB)

    Hadley, Stanton W. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Sanstad, Alan H. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2015-01-01

    Will demand resources such as energy efficiency (EE), demand response (DR), and distributed generation (DG) have an impact on electricity transmission requirements? Five drivers for transmission expansion are discussed: interconnection, reliability, economics, replacement, and policy. With that background, we review the results of a set of transmission studies that were conducted between 2010 and 2013 by electricity regulators, industry representatives, and other stakeholders in the three physical interconnections within the United States. These broad-based studies were funded by the US Department of Energy and included scenarios of reduced load growth due to EE, DR, and DG. While the studies were independent and used different modeling tools and interconnect-specific assumptions, all provided valuable results and insights. However, some caveats exist. Demand resources were evaluated in conjunction with other factors, and limitations on transmission additions between scenarios made understanding the role of demand resources difficult. One study, the western study, included analyses over both 10- and 20-year planning horizons; the 10-year analysis did not show near-term reductions in transmission, but the 20-year indicated fewer transmission additions, yielding a 36percent capital cost reduction. In the eastern study the reductions in demand largely led to reductions in local generation capacity and an increased opportunity for low-cost and renewable generation to export to other regions. The Texas study evaluated generation changes due to demand, and is in the process of examining demand resource impacts on transmission.

  1. Flexible demand in the GB domestic electricity sector in 2030

    International Nuclear Information System (INIS)

    Drysdale, Brian; Wu, Jianzhong; Jenkins, Nick

    2015-01-01

    Highlights: • Annual domestic demand by category and daily flexible load profiles are shown to 2030. • Valuable flexible demand requires loads to be identifiable, accessible, and useful. • The extent of flexible demand varies significantly on a diurnal and seasonal basis. • Barriers to accessing domestic demand include multiple low value loads and apathy. • Existing market structure a barrier to fully rewarding individual load flexibility. - Abstract: In order to meet greenhouse gas emissions targets the Great Britain (GB) future electricity supply will include a higher fraction of non-dispatchable generation, increasing opportunities for demand side management to maintain a supply/demand balance. This paper examines the extent of flexible domestic demand (FDD) in GB, its usefulness in system balancing and appropriate incentives to encourage consumers to participate. FDD, classified as electric space and water heating (ESWH), and cold and wet appliances, amounts to 59 TW h in 2012 (113 TW h total domestic demand) and is calculated to increase to 67 TW h in 2030. Summer and winter daily load profiles for flexible loads show significant seasonal and diurnal variations in the total flexible load and between load categories. Low levels of reflective consumer engagement with electricity consumption and a resistance to automation present barriers to effective access to FDD. A value of £1.97/household/year has been calculated for cold appliance loads used for frequency response in 2030, using 2013 market rates. The introduction of smart meters in GB by 2020 will allow access to FDD for system balancing. The low commercial value of individual domestic loads increases the attractiveness of non-financial incentives to fully exploit FDD. It was shown that appliance loads have different characteristics which can contribute to an efficient power system in different ways

  2. Forecast electricity demand in Quebec: Development plan 1993

    International Nuclear Information System (INIS)

    1992-01-01

    Demographic, economic, and energy prospects are the determining factors in estimating demand for electricity in Quebec. In average scenarios developed for 1992-2010, the Quebec population will grow 0.5%/y and the gross domestic product will increase 2.6%/y. Firm electricity sales by Hydro-Quebec will grow to 197.9 TWh by 2010, or 2.2%/y. Sales in the residential and farm sectors should grow 1.3%/y and sales in the general and institutional sectors should rise by 2.2%/y. Electricity demand in the industrial sector, rising at an estimated 2.9%/y in 1992-2010, is chiefly responsible for the anticipated growth in Hydro-Quebec's overall sales. The nonferrous smelting, refining, chemicals, and paper industries will account for ca 60% of this growth. In the municipal services and public transportation sectors, demand should grow 3.3%/y, and over half the growth forecast in this sector can be attributed to the impact that new uses of electricity are expected to have after 2005. High- and low-growth scenarios offer alternative visions of demand growth based on different but equally valid assumptions about demographic and economic growth. In terms of firm electricity sales, the high- and low-growth scenarios differ by 50 TWh in 2010. Hydro-Quebec has retained two strategic orientations that will influence growth in electricity sales: the development of industrial markets and extension of the energy-savings objective of 9.3 TWh forecast to the year 2000. Taking these two orientations into account, the growth rate for electricity sales in the average scenario would be 1.8%/y rather than 2.2%/y. 25 figs., 81 tabs

  3. Aggregate electricity demand in South Africa: Conditional forecasts to 2030

    Energy Technology Data Exchange (ETDEWEB)

    Inglesi, Roula [Department of Economics, Faculty of Economic and Management Sciences, University of Pretoria, Main Campus, Pretoria 0002 (South Africa)

    2010-01-15

    In 2008, South Africa experienced a severe electricity crisis. Domestic and industrial electricity users had to suffer from black outs all over the country. It is argued that partially the reason was the lack of research on energy, locally. However, Eskom argues that the lack of capacity can only be solved by building new power plants. The objective of this study is to specify the variables that explain the electricity demand in South Africa and to forecast electricity demand by creating a model using the Engle-Granger methodology for co-integration and Error Correction models. By producing reliable results, this study will make a significant contribution that will improve the status quo of energy research in South Africa. The findings indicate that there is a long run relationship between electricity consumption and price as well as economic growth/income. The last few years in South Africa, price elasticity was rarely taken into account because of the low and decreasing prices in the past. The short-run dynamics of the system are affected by population growth, too After the energy crisis, Eskom, the national electricity supplier, is in search for substantial funding in order to build new power plants that will help with the envisaged lack of capacity that the company experienced. By using two scenarios for the future of growth, this study shows that the electricity demand will drop substantially due to the price policies agreed - until now - by Eskom and the National Energy Regulator South Africa (NERSA) that will affect the demand for some years. (author)

  4. Aggregate electricity demand in South Africa: Conditional forecasts to 2030

    International Nuclear Information System (INIS)

    Inglesi, Roula

    2010-01-01

    In 2008, South Africa experienced a severe electricity crisis. Domestic and industrial electricity users had to suffer from black outs all over the country. It is argued that partially the reason was the lack of research on energy, locally. However, Eskom argues that the lack of capacity can only be solved by building new power plants. The objective of this study is to specify the variables that explain the electricity demand in South Africa and to forecast electricity demand by creating a model using the Engle-Granger methodology for co-integration and Error Correction models. By producing reliable results, this study will make a significant contribution that will improve the status quo of energy research in South Africa. The findings indicate that there is a long run relationship between electricity consumption and price as well as economic growth/income. The last few years in South Africa, price elasticity was rarely taken into account because of the low and decreasing prices in the past. The short-run dynamics of the system are affected by population growth, too After the energy crisis, Eskom, the national electricity supplier, is in search for substantial funding in order to build new power plants that will help with the envisaged lack of capacity that the company experienced. By using two scenarios for the future of growth, this study shows that the electricity demand will drop substantially due to the price policies agreed - until now - by Eskom and the National Energy Regulator South Africa (NERSA) that will affect the demand for some years. (author)

  5. Analyses of demand response in Denmark[Electricity market

    Energy Technology Data Exchange (ETDEWEB)

    Moeller Andersen, F.; Grenaa Jensen, S.; Larsen, Helge V.; Meibom, P.; Ravn, H.; Skytte, K.; Togeby, M.

    2006-10-15

    Due to characteristics of the power system, costs of producing electricity vary considerably over short time intervals. Yet, many consumers do not experience corresponding variations in the price they pay for consuming electricity. The topic of this report is: are consumers willing and able to respond to short-term variations in electricity prices, and if so, what is the social benefit of consumers doing so? Taking Denmark and the Nord Pool market as a case, the report focuses on what is known as short-term consumer flexibility or demand response in the electricity market. With focus on market efficiency, efficient allocation of resources and security of supply, the report describes demand response from a micro-economic perspective and provides empirical observations and case studies. The report aims at evaluating benefits from demand response. However, only elements contributing to an overall value are presented. In addition, the analyses are limited to benefits for society, and costs of obtaining demand response are not considered. (au)

  6. An assessment of the influence of demand response on demand elasticity in electricity retail market

    NARCIS (Netherlands)

    Fonteijn, R.; Babar, M.; Kamphuis, I.G.

    2015-01-01

    A transition towards a sustainable society is currently ongoing. In the electrical power system, this is reflected by the increasing share of renewable energy sources (RES). The weather dependence of some RES results in intermittent and volatile behaviour, thus matching supply and demand has become

  7. The role of hydropower in meeting Turkey's electric energy demand

    International Nuclear Information System (INIS)

    Yuksek, Omer; Komurcu, Murat Ihsan; Yuksel, Ibrahim; Kaygusuz, Kamil

    2006-01-01

    The inherent technical, economic and environmental benefits of hydroelectric power, make it an important contributor to the future world energy mix, particularly in the developing countries. These countries, such as Turkey, have a great and ever-intensifying need for power and water supplies and they also have the greatest remaining hydro potential. From the viewpoint of energy sources such as petroleum and natural gas, Turkey is not a rich country; but it has an abundant hydropower potential to be used for generation of electricity and must increase hydropower production in the near future. This paper deals with policies to meet the increasing electricity demand for Turkey. Hydropower and especially small hydropower are emphasized as Turkey's renewable energy sources. The results of two case studies, whose results were not taken into consideration in calculating Turkey's hydro electric potential, are presented. Turkey's small hydro power potential is found to be an important energy source, especially in the Eastern Black Sea Region. The results of a study in which Turkey's long-term demand has been predicted are also presented. According to the results of this paper, Turkey's hydro electric potential can meet 33-46% of its electric energy demand in 2020 and this potential may easily and economically be developed

  8. Households' hourly electricity consumption and peak demand in Denmark

    DEFF Research Database (Denmark)

    Møller Andersen, Frits; Baldini, Mattia; Hansen, Lars Gårn

    2017-01-01

    consumption, we analyse the contribution of appliances and new services, such as individual heat pumps and electric vehicles, to peak consumption and the need for demand response incentives to reduce the peak.Initially, the paper presents a new model that represents the hourly electricity consumption profile...... of households in Denmark. The model considers hourly consumption profiles for different household appliances and their contribution to annual household electricity consumption. When applying the model to an official scenario for annual electricity consumption, assuming non-flexible consumption due...... to a considerable introduction of electric vehicles and individual heat pumps, household consumption is expected to increase considerably, especially peak hour consumption is expected to increase.Next the paper presents results from a new experiment where household customers are given economic and/or environmental...

  9. Electricity demand and basic needs: Empirical evidence from China's households

    International Nuclear Information System (INIS)

    He, Xiaoping; Reiner, David

    2016-01-01

    An increasing block tariff (IBT) has been implemented nationwide in the residential sector in China since 2012. However, knowledge about IBT design is still limited, particularly how to determine the electricity volume for the first block of an IBT scheme. Assuming the first block should be set based on some measure of electricity poverty; we attempt to model household electricity demand such that the range of basic needs can be established. We show that in Chinese households there exists a threshold for electricity consumption with respect to income, which could be considered a measure of electricity poverty, and the threshold differs between rural and urban areas. For rural (urban) families, electricity consumption at the level of 7th (5th) income decile households can be considered the threshold for basic needs or a measure of electricity poverty since household electricity demand in rural (urban) areas does not respond to income changes until after 7th (5th) income decile. Accordingly, the first IBT block for some provinces (e.g., Beijing) appears to have been set at a level that is too high. Over time however, given continued rapid growth, the IBT will begin to better reflect actual basic needs. - Highlights: • Basic electricity needs of a household are investigated with survey data. • The Basic electricity needs differ between the rural and urban households. • The first block of the IBTs in China has proven too high and beyond the basic needs. • The initial policy targets of the IBTs in China will be difficult to achieve.

  10. Labor demand effects of rising electricity prices: Evidence for Germany

    International Nuclear Information System (INIS)

    Cox, Michael; Peichl, Andreas; Pestel, Nico; Siegloch, Sebastian

    2014-01-01

    Germany continues to play a pioneering role in replacing conventional power plants with renewable energy sources. While this might be beneficial with respect to environmental quality, it also implies increasing electricity prices. The extent to which this is associated with negative impacts on employment depends on the interrelationship between labor and electricity as input factors in the production process. In this paper, we estimate cross-price elasticities between electricity and heterogeneous labor for the German manufacturing sector. We use administrative linked employer–employee micro-data combined with information on sector-level electricity prices and usage over the period 2003–2007. We find positive, but small conditional cross-price elasticities of labor demand with respect to electricity prices, which means that electricity as an input factor can be replaced by labor to a limited extent when the production level is held constant. In the case of adjustable output, we find negative unconditional cross-price elasticities, implying that higher electricity prices lead to output reductions and to lower labor demand, with low- and high-skilled workers being affected more than medium-skilled. Resulting adverse distributional effects and potential overall job losses may pose challenges for policy-makers in securing public support for the German energy turnaround. - Highlights: • We estimate cross-price elasticities for electricity and labor in manufacturing. • We use linked employer–employee micro-data from Germany for 2003 to 2007. • We find a weak substitutability between electricity and labor for constant output. • We find complementarity between electricity and labor for adjustable output. • Low- and high-skilled workers are more affected than medium-skilled

  11. Residential demand response reduces air pollutant emissions on peak electricity demand days in New York City

    International Nuclear Information System (INIS)

    Gilbraith, Nathaniel; Powers, Susan E.

    2013-01-01

    Many urban areas in the United States have experienced difficulty meeting the National Ambient Air Quality Standards (NAAQS), partially due to pollution from electricity generating units. We evaluated the potential for residential demand response to reduce pollutant emissions on days with above average pollutant emissions and a high potential for poor air quality. The study focused on New York City (NYC) due to non-attainment with NAAQS standards, large exposed populations, and the existing goal of reducing pollutant emissions. The baseline demand response scenario simulated a 1.8% average reduction in NYC peak demand on 49 days throughout the summer. Nitrogen oxide and particulate matter less than 2.5 μm in diameter emission reductions were predicted to occur (−70, −1.1 metric tons (MT) annually), although, these were not likely to be sufficient for NYC to meet the NAAQS. Air pollution mediated damages were predicted to decrease by $100,000–$300,000 annually. A sensitivity analysis predicted that substantially larger pollutant emission reductions would occur if electricity demand was shifted from daytime hours to nighttime hours, or the total consumption decreased. Policies which incentivize shifting electricity consumption away from periods of high human and environmental impacts should be implemented, including policies directed toward residential consumers. - Highlights: • The impact of residential demand response on air emissions was modeled. • Residential demand response will decrease pollutant emissions in NYC. • Emissions reductions occur during periods with high potential for poor air quality. • Shifting demand to nighttime hours was more beneficial than to off-peak daytime hours

  12. Deregulation of Electricity Market and Drivers of Demand for Electrical Energy in Industry

    Directory of Open Access Journals (Sweden)

    Bojnec Štefan

    2016-09-01

    Full Text Available This paper investigates deregulation of electricity market focusing on electricity prices and drivers of demand for electrical energy in industry in Slovenia. The patterns in evolution of real electricity price developments and the three main components of the electricity price are calculated: liberalized market share for purchased electricity price, regulated infrastructure share for use of electricity network grids and mandatory state charges in the sale of electricity (duty, excise duty and value-added tax. To calculate the real value of electricity prices, producer price index of industrial commodities for electricity prices in industry is used as deflator and implicit deflator of gross domestic product for the size of the economy. In the empirical econometric part is used regression analysis for the amount electricity consumption in the industry depending on the real gross domestic product, direct and cross-price elasticity for natural gas prices in the industry. The results confirmed volatility in real electricity price developments with their increasing tendency and the increasing share of different taxes and state charges in the electricity prices for industry. Demand for electrical energy in industry is positively associated with gross domestic product and price of natural gas as substitute for electrical energy in industry use, and negatively associated with prices of electrical energy for industry.

  13. A subjective supply–demand model: the maximum Boltzmann/Shannon entropy solution

    International Nuclear Information System (INIS)

    Piotrowski, Edward W; Sładkowski, Jan

    2009-01-01

    The present authors have put forward a projective geometry model of rational trading. The expected (mean) value of the time that is necessary to strike a deal and the profit strongly depend on the strategies adopted. A frequent trader often prefers maximal profit intensity to the maximization of profit resulting from a separate transaction because the gross profit/income is the adopted/recommended benchmark. To investigate activities that have different periods of duration we define, following the queuing theory, the profit intensity as a measure of this economic category. The profit intensity in repeated trading has a unique property of attaining its maximum at a fixed point regardless of the shape of demand curves for a wide class of probability distributions of random reverse transactions (i.e. closing of the position). These conclusions remain valid for an analogous model based on supply analysis. This type of market game is often considered in research aiming at finding an algorithm that maximizes profit of a trader who negotiates prices with the Rest of the World (a collective opponent), possessing a definite and objective supply profile. Such idealization neglects the sometimes important influence of an individual trader on the demand/supply profile of the Rest of the World and in extreme cases questions the very idea of demand/supply profile. Therefore we put forward a trading model in which the demand/supply profile of the Rest of the World induces the (rational) trader to (subjectively) presume that he/she lacks (almost) all knowledge concerning the market but his/her average frequency of trade. This point of view introduces maximum entropy principles into the model and broadens the range of economic phenomena that can be perceived as a sort of thermodynamical system. As a consequence, the profit intensity has a fixed point with an astonishing connection with Fibonacci classical works and looking for the quickest algorithm for obtaining the extremum of a

  14. A subjective supply-demand model: the maximum Boltzmann/Shannon entropy solution

    Science.gov (United States)

    Piotrowski, Edward W.; Sładkowski, Jan

    2009-03-01

    The present authors have put forward a projective geometry model of rational trading. The expected (mean) value of the time that is necessary to strike a deal and the profit strongly depend on the strategies adopted. A frequent trader often prefers maximal profit intensity to the maximization of profit resulting from a separate transaction because the gross profit/income is the adopted/recommended benchmark. To investigate activities that have different periods of duration we define, following the queuing theory, the profit intensity as a measure of this economic category. The profit intensity in repeated trading has a unique property of attaining its maximum at a fixed point regardless of the shape of demand curves for a wide class of probability distributions of random reverse transactions (i.e. closing of the position). These conclusions remain valid for an analogous model based on supply analysis. This type of market game is often considered in research aiming at finding an algorithm that maximizes profit of a trader who negotiates prices with the Rest of the World (a collective opponent), possessing a definite and objective supply profile. Such idealization neglects the sometimes important influence of an individual trader on the demand/supply profile of the Rest of the World and in extreme cases questions the very idea of demand/supply profile. Therefore we put forward a trading model in which the demand/supply profile of the Rest of the World induces the (rational) trader to (subjectively) presume that he/she lacks (almost) all knowledge concerning the market but his/her average frequency of trade. This point of view introduces maximum entropy principles into the model and broadens the range of economic phenomena that can be perceived as a sort of thermodynamical system. As a consequence, the profit intensity has a fixed point with an astonishing connection with Fibonacci classical works and looking for the quickest algorithm for obtaining the extremum of a

  15. Two-Stage Electricity Demand Modeling Using Machine Learning Algorithms

    Directory of Open Access Journals (Sweden)

    Krzysztof Gajowniczek

    2017-10-01

    Full Text Available Forecasting of electricity demand has become one of the most important areas of research in the electric power industry, as it is a critical component of cost-efficient power system management and planning. In this context, accurate and robust load forecasting is supposed to play a key role in reducing generation costs, and deals with the reliability of the power system. However, due to demand peaks in the power system, forecasts are inaccurate and prone to high numbers of errors. In this paper, our contributions comprise a proposed data-mining scheme for demand modeling through peak detection, as well as the use of this information to feed the forecasting system. For this purpose, we have taken a different approach from that of time series forecasting, representing it as a two-stage pattern recognition problem. We have developed a peak classification model followed by a forecasting model to estimate an aggregated demand volume. We have utilized a set of machine learning algorithms to benefit from both accurate detection of the peaks and precise forecasts, as applied to the Polish power system. The key finding is that the algorithms can detect 96.3% of electricity peaks (load value equal to or above the 99th percentile of the load distribution and deliver accurate forecasts, with mean absolute percentage error (MAPE of 3.10% and resistant mean absolute percentage error (r-MAPE of 2.70% for the 24 h forecasting horizon.

  16. Australia's long-term electricity demand forecasting using deep neural networks

    OpenAIRE

    Hamedmoghadam, Homayoun; Joorabloo, Nima; Jalili, Mahdi

    2018-01-01

    Accurate prediction of long-term electricity demand has a significant role in demand side management and electricity network planning and operation. Demand over-estimation results in over-investment in network assets, driving up the electricity prices, while demand under-estimation may lead to under-investment resulting in unreliable and insecure electricity. In this manuscript, we apply deep neural networks to predict Australia's long-term electricity demand. A stacked autoencoder is used in...

  17. Dynamic linear modeling of monthly electricity demand in Japan: Time variation of electricity conservation effect.

    Science.gov (United States)

    Honjo, Keita; Shiraki, Hiroto; Ashina, Shuichi

    2018-01-01

    After the severe nuclear disaster in Fukushima, which was triggered by the Great East Japan earthquake in March 2011, nuclear power plants in Japan were temporarily shut down for mandatory inspections. To prevent large-scale blackouts, the Japanese government requested companies and households to reduce electricity consumption in summer and winter. It is reported that the domestic electricity demand had a structural decrease because of the electricity conservation effect (ECE). However, quantitative analysis of the ECE is not sufficient, and especially time variation of the ECE remains unclear. Understanding the ECE is important because Japan's NDC (nationally determined contribution) assumes the reduction of CO2 emissions through aggressive energy conservation. In this study, we develop a time series model of monthly electricity demand in Japan and estimate time variation of the ECE. Moreover, we evaluate the impact of electricity conservation on CO2 emissions from power plants. The dynamic linear model is used to separate the ECE from the effects of other irrelevant factors (e.g. air temperature, economic production, and electricity price). Our result clearly shows that consumers' electricity conservation behavior after the earthquake was not temporary but became established as a habit. Between March 2011 and March 2016, the ECE on industrial electricity demand ranged from 3.9% to 5.4%, and the ECE on residential electricity demand ranged from 1.6% to 7.6%. The ECE on the total electricity demand was estimated at 3.2%-6.0%. We found a seasonal pattern that the residential ECE in summer is higher than that in winter. The emissions increase from the shutdown of nuclear power plants was mitigated by electricity conservation. The emissions reduction effect was estimated at 0.82 MtCO2-2.26 MtCO2 (-4.5% on average compared to the zero-ECE case). The time-varying ECE is necessary for predicting Japan's electricity demand and CO2 emissions after the earthquake.

  18. Bayesian Analysis of Demand Elasticity in the Italian Electricity Market

    Directory of Open Access Journals (Sweden)

    Maria Chiara D'Errico

    2015-09-01

    Full Text Available The liberalization of the Italian electricity market is a decade old. Within these last ten years, the supply side has been extensively analyzed, but not the demand side. The aim of this paper is to provide a new method for estimation of the demand elasticity, based on Bayesian methods applied to the Italian electricity market. We used individual demand bids data in the day-ahead market in the Italian Power Exchange (IPEX, for 2011, in order to construct an aggregate demand function at the hourly level. We took into account the existence of both elastic and inelastic bidders on the demand side. The empirical results show that elasticity varies significantly during the day and across periods of the year. In addition, the elasticity hourly distribution is clearly skewed and more so in the daily hours. The Bayesian method is a useful tool for policy-making, insofar as the regulator can start with a priori historical information on market behavior and estimate actual market outcomes in response to new policy actions.

  19. An Analysis on change of household electricity demand pattern

    Energy Technology Data Exchange (ETDEWEB)

    Na, In Gang [Korea Energy Economics Institute, Euiwang (Korea)

    1999-01-01

    The object of this study is to analyze the behavioral pattern change of household electricity demand. Through the cross section analysis using materials from the energy total research report, the change in income elasticity of household electricity demand was studied. In this study, two methodologies were used. Firstly, it was shown that the effect of an income variable was very significant with a positive value in simultaneous equations model using exponential equations of electrical appliances holding. Cross section income effect showed a various distribution according to the season or income level. Overall, it was calculated at 0.111 when the appliances are fixed and 0.432 when even appliances are changed. Secondly, using a choice convenient correction model, it is resulted that lambda, the choice convenient correction factor, has a positive value and is statistically significant. In 1996, income elasticity of electricity demand for households with air-conditioning was 0.305 and for households without air-conditioning was 0.172. Income elasticity of households with air-conditioning is increasing as time goes by while income elasticity of households without air-conditioning is decreasing. (author). 32 refs., 35 tabs.

  20. Demand for electric power in major markets worldwide

    Energy Technology Data Exchange (ETDEWEB)

    Roeder, A [ABB Asea Brown Boveri Ltd., Zurich (Switzerland)

    1990-01-01

    One third of primary energy consumption is today being used to generate electrical power. The author discusses with the aid of statistics and diagrams, the various uses of energy, and the per capita energy consumption throughout the world. He considers that future demand for power depends to a large extent on GNP but also on fuel prices and reserves, energy policies and environmental concerns. On balance, these will lead to the introduction of clean coal technologies and a renaissance of nuclear power stations in the near future but until then gas-fired power plant will continue to play a dominant role in meeting power demands. 9 figs., 8 tabs.

  1. Energy and electricity demand forecasting for nuclear power planning in developing countries

    International Nuclear Information System (INIS)

    1988-07-01

    This Guidebook is designed to be a reference document to forecast energy and electricity demand. It presents concepts and methodologies that have been developed to make an analytical approach to energy/electricity demand forecasting as part of the planning process. The Guidebook is divided into 6 main chapters: (Energy demand and development, energy demand analysis, electric load curve analysis, energy and electricity demand forecasting, energy and electricity demand forecasting tools used in various organizations, IAEA methodologies for energy and electricity demand forecasting) and 3 appendices (experience with case studies carried out by the IAEA, reference technical data, reference economic data). A bibliography and a glossary complete the Guidebook. Refs, figs and tabs

  2. Managing electrical demand through difficult periods: California's experience with demand response

    International Nuclear Information System (INIS)

    Wikler, G.; Ghosh, D.Ph.D.

    2010-01-01

    This paper provides a brief overview of California's electricity situation and the relevance of Demand Response (DR) in addressing some of the challenges faced by the State's electricity system. It then discusses California's experience with DR, market rules that influence what role DR plays and attempts to integrate wholesale-retail level program offerings in the State, and some of the key drivers that are likely to enhance the role of DR. Lastly, the paper identifies some of the key challenges facing implementers of DR programs and discusses how many of those challenges could potentially be overcome. (authors)

  3. Demand Response in U.S. Electricity Markets: Empirical Evidence

    OpenAIRE

    Cappers, Peter

    2009-01-01

    Empirical evidence concerning demand response (DR) resources is needed in order to establish baseline conditions, develop standardized methods to assess DR availability and performance, and to build confidence among policymakers, utilities, system operators, and stakeholders that DR resources do offer a viable, cost-effective alternative to supply-side investments. This paper summarizes the existing contribution of DR resources in U.S. electric power markets. In 2008, customers enrolled in ...

  4. Production in Italian industry: Electric power demand indicators

    International Nuclear Information System (INIS)

    Ajello, V.

    1993-01-01

    The effects of the recession in Italy were first evidenced during the period spanning 1990-1992 with a sharp drop in the international competitiveness of Italian products. This phase was then followed by a significant drop in internal demand, the devaluation of the Italian Lira and subsequent market uncertainty. This paper presents graphs of national and regional electric power production and consumption figures which reflect the downturn in the viability of the Italian economy, especially in the industrial sector

  5. FACTORS DECREASING HOUSEHOLD ELECTRICITY DEMAND – A QUALITATIVE APPROACH

    Directory of Open Access Journals (Sweden)

    Shimon ELBAZ

    2018-05-01

    Full Text Available Reducing energy consumption through changes in individual consumers’ behaviors is one of the most important challenges of the present society and near future. Our qualitative study, based on semi-structured interviews, deals with the investigation of household consumer behavior, in order to explore ways for reducing the electricity demand, in the particular cultural context of a country with high levels of energy consumption in both summer and winter times – Israel. Various approaches, coming from economics, sociology, psychology or education were tested, for limiting the use of a particular, invisible and intangible merchandise - electricity. The main objective of the present study was to determine consumers’ perceptions about the various approaches that could be used to decrease the domestic demand and consumption of electricity. A secondary objective was to identify, based on consumers’ perceptions, the factors of influence that could be used in future quantitative researches and governance strategies. We found out that investigated families have a high level of education in the field of electricity consumption and marketing campaigns, which would make the classic energy educational approach less efficient. Household electricity consumers in Israel have awareness and willingness not to waste or consume electricity beyond what is necessary, but the necessary level is positioned quite high. The social comparison approach appears to be ineffective, as well, even if it proved its efficiency in other cultures. The psychological and the economic approach could be partially efficient, if certain influence factors are widely used. These factors include mainly the magnitude of the savings, the perceived behavioral control, the personal thermal comfort and the pro-environmental attitude. The most important managerial implication concerns the strategies that could be conceived by electricity companies and national authorities – based on un

  6. Spatial analysis of the electrical energy demand in Greece

    International Nuclear Information System (INIS)

    Tyralis, Hristos; Mamassis, Nikos; Photis, Yorgos N.

    2017-01-01

    The Electrical Energy Demand (EED) of the agricultural, commercial and industrial sector in Greece, as well as its use for domestic activities, public and municipal authorities and street lighting are analysed spatially using Geographical Information System and spatial statistical methods. The analysis is performed on data which span from 2008 to 2012 and have annual temporal resolution and spatial resolution down to the NUTS (Nomenclature of Territorial Units for Statistics) level 3. The aim is to identify spatial patterns of the EED and its transformations such as the ratios of the EED to socioeconomic variables, i.e. the population, the total area, the population density and the Gross Domestic Product (GDP). Based on the analysis, Greece is divided in five regions, each one with a different development model, i.e. Attica and Thessaloniki which are two heavily populated major poles, Thessaly and Central Greece which form a connected geographical region with important agricultural and industrial sector, the islands and some coastal areas which are characterized by an important commercial sector and the rest Greek areas. The spatial patterns can provide additional information for policy decision about the electrical energy management and better representation of the regional socioeconomic conditions. - Highlights: • We visualize spatially the Electrical Energy Demand (EED) in Greece. • We apply spatial analysis methods to the EED data. • Spatial patterns of the EED are identified. • Greece is classified in five distinct groups, based on the analysis. • The results can be used for optimal planning of the electric system.

  7. Hourly price elasticity pattern of electricity demand in the German day-ahead market

    OpenAIRE

    Knaut, Andreas; Paulus, Simon

    2016-01-01

    System security in electricity markets relies crucially on the interaction between demand and supply over time. However, research on electricity markets has been mainly focusing on the supply side arguing that demand is rather inelastic. Assuming perfectly inelastic demand might lead to delusive statements regarding the price formation in electricity markets. In this article we quantify the short-run price elasticity of electricity demand in the German day-ahead market and show that demand is...

  8. The flexibility of household electricity demand over time

    International Nuclear Information System (INIS)

    Halvorsen, B.; Larsen, B.M.

    2001-01-01

    Empirical estimates of long run effects on residential electricity demand from changes in the electricity price are usually estimated by cross-sectional variation in the current stock of electric household appliances across households at a certain point in time. Here, we use a discrete-continuous approach modeling the long run effects by investments in new appliances. We apply the annual Norwegian Survey of Consumer Expenditure for the period 1975 to 1994 to estimate the short and long run own price elasticities in the two approaches. We find the estimated long run elasticity only slightly more price elastic than the short run. We also find that the long run elasticity does not differ significantly between the two approaches. The reason for both results is that, since there is no alternative source of energy for these appliances, there are no substitution effects

  9. Aligning PEV Charging Times with Electricity Supply and Demand

    Energy Technology Data Exchange (ETDEWEB)

    Hodge, Cabell [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2017-06-05

    Plug-in electric vehicles (PEVs) are a growing source of electricity consumption that could either exacerbate supply shortages or smooth electricity demand curves. Extensive research has explored how vehicle-grid integration (VGI) can be optimized by controlling PEV charging timing or providing vehicle-to-grid (V2G) services, such as storing energy in vehicle batteries and returning it to the grid at peak times. While much of this research has modeled charging, implementation in the real world requires a cost-effective solution that accounts for consumer behavior. To function across different contexts, several types of charging administrators and methods of control are necessary to minimize costs in the VGI context.

  10. Medium-term electric power demand forecasting based on economic-electricity transmission model

    Science.gov (United States)

    Li, Wenfeng; Bao, Fangmin; Bai, Hongkun; Liu, Wei; Liu, Yongmin; Mao, Yubin; Wang, Jiangbo; Liu, Junhui

    2018-06-01

    Electric demand forecasting is a basic work to ensure the safe operation of power system. Based on the theories of experimental economics and econometrics, this paper introduces Prognoz Platform 7.2 intelligent adaptive modeling platform, and constructs the economic electricity transmission model that considers the economic development scenarios and the dynamic adjustment of industrial structure to predict the region's annual electricity demand, and the accurate prediction of the whole society's electricity consumption is realized. Firstly, based on the theories of experimental economics and econometrics, this dissertation attempts to find the economic indicator variables that drive the most economical growth of electricity consumption and availability, and build an annual regional macroeconomic forecast model that takes into account the dynamic adjustment of industrial structure. Secondly, it innovatively put forward the economic electricity directed conduction theory and constructed the economic power transfer function to realize the group forecast of the primary industry + rural residents living electricity consumption, urban residents living electricity, the second industry electricity consumption, the tertiary industry electricity consumption; By comparing with the actual value of economy and electricity in Henan province in 2016, the validity of EETM model is proved, and the electricity consumption of the whole province from 2017 to 2018 is predicted finally.

  11. Hybrid systems to address seasonal mismatches between electricity production and demand in nuclear renewable electrical grids

    International Nuclear Information System (INIS)

    Forsberg, Charles

    2013-01-01

    A strategy to enable zero-carbon variable electricity production with full utilization of renewable and nuclear energy sources has been developed. Wind and solar systems send electricity to the grid. Nuclear plants operate at full capacity with variable steam to turbines to match electricity demand with production (renewables and nuclear). Excess steam at times of low electricity prices and electricity demand go to hybrid fuel production and storage systems. The characteristic of these hybrid technologies is that the economic penalties for variable nuclear steam inputs are small. Three hybrid systems were identified that could be deployed at the required scale. The first option is the gigawatt-year hourly-to-seasonal heat storage system where excess steam from the nuclear plant is used to heat rock a kilometer underground to create an artificial geothermal heat source. The heat source produces electricity on demand using geothermal technology. The second option uses steam from the nuclear plant and electricity from the grid with high-temperature electrolysis (HTR) cells to produce hydrogen and oxygen. Hydrogen is primarily for industrial applications; however, the HTE can be operated in reverse using hydrogen for peak electricity production. The third option uses variable steam and electricity for shale oil production. -- Highlights: •A system is proposed to meet variable hourly to seasonal electricity demand. •Variable solar and wind electricity sent to the grid. •Base-load nuclear plants send variable steam for electricity and hybrid systems. •Hybrid energy systems can economically absorb gigawatts of variable steam. •Hybrid systems include geothermal heat storage, hydrogen, and shale-oil production

  12. Demand response in liberalized electricity markets - the Nordic case

    International Nuclear Information System (INIS)

    Bjoerndal, Mette; Lund, Arne-Christian; Rud, Linda

    2005-01-01

    The liberalization of the Nordic electricity markets started with the deregulation of the Norwegian market, and the later inclusion of Sweden, Denmark and Finland in The Nord Pool area has provided a truly international marketplace, where prices are quoted for all the Nordic countries except Iceland. The structure of the Norwegian supply side was a favorable starting point for the liberalization process with many independent (hydropower) producers and, following the Energy Act of 1991, the vertical separation of competitive production on the one hand and regulated transmission / distribution one the other hand (implemented as a requirement of separation of financial accounts). Moreover, since the mid 1990s (unregulated) retail competition has provided market based price-signals to customers, even to individual households. In this paper we will focus on the potential benefits of demand flexibility in order to enhance the performance of the electricity market in attaining optimal operation and development of the electricity system. These benefits will depend on the price elasticity of the demand. However, whether it is possible to act on price changes also depends on the information provided to and from the customers. Especially for short run flexibility, this may require two way communication devises for larger customer groups, which raises questions like who is to pay for the investments needed, and who will benefit from them. Demand response also depends on the marginal signals resulting from the different contracts offered to the customers. Today this includes ''variable'' price, spot price (based on Nord Pool Elspot) and fixed price contracts. Customer flexibility depends on the possibility of substitution for instance to other fuels / alternative energy provisions. Finally, flexibility will differ between customer classes, for instance households, industry, power intensive industry etc. In this paper we investigate demand response and customer flexibility in

  13. Quantifying the Flexibility of Residential Electricity Demand in 2050: a Bottom-Up Approach

    OpenAIRE

    van Stiphout, Arne; Engels, Jonas; Guldentops, Dries; Deconinck, Geert

    2015-01-01

    This work presents a new method to quantify the flexibility of automatic demand response applied to residential electricity demand using price elasticities. A stochastic bottom-up model of flexible electricity demand in 2050 is presented. Three types of flexible devices are implemented: electrical heating, electric vehicles and wet appliances. Each house schedules its flexible demand w.r.t. a varying price signal, in order to minimize electricity cost. Own- and cross-price elasticities are ob...

  14. The analysis of Taiwan's residential electricity demand under the electricity tariff policy

    Science.gov (United States)

    Chen, Po-Jui

    In October 2013, the Taiwan Power Company (Taipower), the monopolized state utility service in Taiwan, implemented an electricity tariff adjustment policy to reduce residential electricity demand. Using bi-monthly billing data from 6,932 electricity consumers, this study examine how consumers respond to an increase in electricity prices. This study employs an empirical approach that takes advantage of quasi-random variation over a period of time when household bills were affected by a change in electricity price. The study found that this price increase caused a 1.78% decline in residential electricity consumption, implying a price elasticity of -0.19 for summer-season months and -0.15 for non-summer-season months. The demand for electricity is therefore relatively inelastic, likely because it is hard for people to change their electricity consumption behavior in the short-term. The results of this study highlight that demand-side management cannot be the only lever used to address Taiwan's forecasted decrease in electricity supply.

  15. Electric Water Heater Modeling and Control Strategies for Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Diao, Ruisheng; Lu, Shuai; Elizondo, Marcelo A.; Mayhorn, Ebony T.; Zhang, Yu; Samaan, Nader A.

    2012-07-22

    Abstract— Demand response (DR) has a great potential to provide balancing services at normal operating conditions and emergency support when a power system is subject to disturbances. Effective control strategies can significantly relieve the balancing burden of conventional generators and reduce investment on generation and transmission expansion. This paper is aimed at modeling electric water heaters (EWH) in households and tests their response to control strategies to implement DR. The open-loop response of EWH to a centralized signal is studied by adjusting temperature settings to provide regulation services; and two types of decentralized controllers are tested to provide frequency support following generator trips. EWH models are included in a simulation platform in DIgSILENT to perform electromechanical simulation, which contains 147 households in a distribution feeder. Simulation results show the dependence of EWH response on water heater usage . These results provide insight suggestions on the need of control strategies to achieve better performance for demand response implementation. Index Terms— Centralized control, decentralized control, demand response, electrical water heater, smart grid

  16. maximum conversion efficiency of thermionic heat to electricity

    African Journals Online (AJOL)

    DJFLEX

    Dushman constant ... Several attempts on the direct conversion of heat to electricity ... The net current density in the system is equal to jE – jC , which gets over the potential barrier. jE and jC are given by the Richardson-. Dushman equation as. │. ⌋.

  17. Demand side management in recycling and electricity retail pricing

    Science.gov (United States)

    Kazan, Osman

    This dissertation addresses several problems from the recycling industry and electricity retail market. The first paper addresses a real-life scheduling problem faced by a national industrial recycling company. Based on their practices, a scheduling problem is defined, modeled, analyzed, and a solution is approximated efficiently. The recommended application is tested on the real-life data and randomly generated data. The scheduling improvements and the financial benefits are presented. The second problem is from electricity retail market. There are well-known patterns in daily usage in hours. These patterns change in shape and magnitude by seasons and days of the week. Generation costs are multiple times higher during the peak hours of the day. Yet most consumers purchase electricity at flat rates. This work explores analytic pricing tools to reduce peak load electricity demand for retailers. For that purpose, a nonlinear model that determines optimal hourly prices is established based on two major components: unit generation costs and consumers' utility. Both are analyzed and estimated empirically in the third paper. A pricing model is introduced to maximize the electric retailer's profit. As a result, a closed-form expression for the optimal price vector is obtained. Possible scenarios are evaluated for consumers' utility distribution. For the general case, we provide a numerical solution methodology to obtain the optimal pricing scheme. The models recommended are tested under various scenarios that consider consumer segmentation and multiple pricing policies. The recommended model reduces the peak load significantly in most cases. Several utility companies offer hourly pricing to their customers. They determine prices using historical data of unit electricity cost over time. In this dissertation we develop a nonlinear model that determines optimal hourly prices with parameter estimation. The last paper includes a regression analysis of the unit generation cost

  18. Dispatchable Hydrogen Production at the Forecourt for Electricity Demand Shaping

    Directory of Open Access Journals (Sweden)

    Abdulla Rahil

    2017-10-01

    Full Text Available Environmental issues and concerns about depletion of fossil fuels have driven rapid growth in the generation of renewable energy (RE and its use in electricity grids. Similarly, the need for an alternative to hydrocarbon fuels means that the number of fuel cell vehicles is also expected to increase. The ability of electricity networks to balance supply and demand is greatly affected by the variable, intermittent output of RE generators; however, this could be relieved using energy storage and demand-side response (DSR techniques. One option would be production of hydrogen by electrolysis powered from wind and solar sources. The use of tariff structures would provide an incentive to operate electrolysers as dispatchable loads. The aim of this paper is to compare the cost of hydrogen production by electrolysis at garage forecourts in Libya, for both dispatchable and continuous operation, without interruption of fuel supply to vehicles. The coastal city of Derna was chosen as a case study, with the renewable energy being produced via a wind turbine farm. Wind speed was analysed in order to determine a suitable turbine, then the capacity was calculated to estimate how many turbines would be needed to meet demand. Finally, the excess power was calculated, based on the discrepancy between supply and demand. The study looked at a hydrogen refueling station in both dispatchable and continuous operation, using an optimisation algorithm. The following three scenarios were considered to determine whether the cost of electrolytic hydrogen could be reduced by a lower off-peak electricity price. These scenarios are: Standard Continuous, in which the electrolyser operates continuously on a standard tariff of 12 p/kWh; Off-peak Only, in which the electrolyser operates only during off-peak periods at the lower price of 5 p/kWh; and 2-Tier Continuous, in which the electrolyser operates continuously on a low tariff at off-peak times and a high tariff at other

  19. Dynamic linear modeling of monthly electricity demand in Japan: Time variation of electricity conservation effect.

    Directory of Open Access Journals (Sweden)

    Keita Honjo

    Full Text Available After the severe nuclear disaster in Fukushima, which was triggered by the Great East Japan earthquake in March 2011, nuclear power plants in Japan were temporarily shut down for mandatory inspections. To prevent large-scale blackouts, the Japanese government requested companies and households to reduce electricity consumption in summer and winter. It is reported that the domestic electricity demand had a structural decrease because of the electricity conservation effect (ECE. However, quantitative analysis of the ECE is not sufficient, and especially time variation of the ECE remains unclear. Understanding the ECE is important because Japan's NDC (nationally determined contribution assumes the reduction of CO2 emissions through aggressive energy conservation. In this study, we develop a time series model of monthly electricity demand in Japan and estimate time variation of the ECE. Moreover, we evaluate the impact of electricity conservation on CO2 emissions from power plants. The dynamic linear model is used to separate the ECE from the effects of other irrelevant factors (e.g. air temperature, economic production, and electricity price. Our result clearly shows that consumers' electricity conservation behavior after the earthquake was not temporary but became established as a habit. Between March 2011 and March 2016, the ECE on industrial electricity demand ranged from 3.9% to 5.4%, and the ECE on residential electricity demand ranged from 1.6% to 7.6%. The ECE on the total electricity demand was estimated at 3.2%-6.0%. We found a seasonal pattern that the residential ECE in summer is higher than that in winter. The emissions increase from the shutdown of nuclear power plants was mitigated by electricity conservation. The emissions reduction effect was estimated at 0.82 MtCO2-2.26 MtCO2 (-4.5% on average compared to the zero-ECE case. The time-varying ECE is necessary for predicting Japan's electricity demand and CO2 emissions after the

  20. Dynamic linear modeling of monthly electricity demand in Japan: Time variation of electricity conservation effect

    Science.gov (United States)

    Shiraki, Hiroto; Ashina, Shuichi

    2018-01-01

    After the severe nuclear disaster in Fukushima, which was triggered by the Great East Japan earthquake in March 2011, nuclear power plants in Japan were temporarily shut down for mandatory inspections. To prevent large-scale blackouts, the Japanese government requested companies and households to reduce electricity consumption in summer and winter. It is reported that the domestic electricity demand had a structural decrease because of the electricity conservation effect (ECE). However, quantitative analysis of the ECE is not sufficient, and especially time variation of the ECE remains unclear. Understanding the ECE is important because Japan’s NDC (nationally determined contribution) assumes the reduction of CO2 emissions through aggressive energy conservation. In this study, we develop a time series model of monthly electricity demand in Japan and estimate time variation of the ECE. Moreover, we evaluate the impact of electricity conservation on CO2 emissions from power plants. The dynamic linear model is used to separate the ECE from the effects of other irrelevant factors (e.g. air temperature, economic production, and electricity price). Our result clearly shows that consumers’ electricity conservation behavior after the earthquake was not temporary but became established as a habit. Between March 2011 and March 2016, the ECE on industrial electricity demand ranged from 3.9% to 5.4%, and the ECE on residential electricity demand ranged from 1.6% to 7.6%. The ECE on the total electricity demand was estimated at 3.2%–6.0%. We found a seasonal pattern that the residential ECE in summer is higher than that in winter. The emissions increase from the shutdown of nuclear power plants was mitigated by electricity conservation. The emissions reduction effect was estimated at 0.82 MtCO2–2.26 MtCO2 (−4.5% on average compared to the zero-ECE case). The time-varying ECE is necessary for predicting Japan’s electricity demand and CO2 emissions after the

  1. Market-based Demand Response via Residential Plug-in Electric Vehicles in Smart Grids

    OpenAIRE

    Rassaei, Farshad; Soh, Wee-Seng; Chua, Kee-Chaing

    2015-01-01

    Flexibility in power demand, diverse usage patterns and storage capability of plug-in electric vehicles (PEVs) grow the elasticity of residential electricity demand remarkably. This elasticity can be utilized to form the daily aggregated demand profile and/or alter instantaneous demand of a system wherein a large number of residential PEVs share one electricity retailer or an aggregator. In this paper, we propose a demand response (DR) technique to manage vehicle-to-grid (V2G) enabled PEVs' e...

  2. State-level electricity demand forecasting model. [For 1980, 1985, 1990

    Energy Technology Data Exchange (ETDEWEB)

    Nguyen, H. D.

    1978-01-01

    This note briefly describes the Oak Ridge National Laboratory (ORNL) state-level electricity demand (SLED) forecasting model developed for the Nuclear Regulatory Commission. Specifically, the note presents (1) the special features of the model, (2) the methodology used to forecast electricity demand, and (3) forecasts of electricity demand and average price by sector for 15 states for 1980, 1985, 1990.

  3. Modeling and forecasting of electrical power demands for capacity planning

    International Nuclear Information System (INIS)

    Al-Shobaki, Salman; Mohsen, Mousa

    2008-01-01

    This paper describes the development of forecasting models to predict future generation and electrical power consumption in Jordan. This is critical to production cost since power is generated by burning expensive imported oil. Currently, the National Electric Power Company (NEPCO) is using regression models that only accounts for trend dynamics in their planning of loads and demand levels. The models are simplistic and are based on generated energy historical levels. They produce results on yearly bases and do not account for monthly variability in demand levels. The paper presents two models, one based on the generated energy data and the other is based on the consumed energy data. The models account for trend, monthly seasonality, and cycle dynamics. Both models are compared to NEPCO's model and indicate that NEPCO is producing energy at levels higher than needed (5.25%) thus increasing the loss in generated energy. The developed models also show a 13% difference between the generated energy and the consumed energy that is lost due to transmission line and in-house consumption

  4. Modeling and forecasting of electrical power demands for capacity planning

    Energy Technology Data Exchange (ETDEWEB)

    Al-Shobaki, Salman [Department of Industrial Engineering, Hashemite University, Zarka 13115 (Jordan); Mohsen, Mousa [Department of Mechanical Engineering, Hashemite University, Zarka 13115 (Jordan)

    2008-11-15

    This paper describes the development of forecasting models to predict future generation and electrical power consumption in Jordan. This is critical to production cost since power is generated by burning expensive imported oil. Currently, the National Electric Power Company (NEPCO) is using regression models that only accounts for trend dynamics in their planning of loads and demand levels. The models are simplistic and are based on generated energy historical levels. They produce results on yearly bases and do not account for monthly variability in demand levels. The paper presents two models, one based on the generated energy data and the other is based on the consumed energy data. The models account for trend, monthly seasonality, and cycle dynamics. Both models are compared to NEPCO's model and indicate that NEPCO is producing energy at levels higher than needed (5.25%) thus increasing the loss in generated energy. The developed models also show a 13% difference between the generated energy and the consumed energy that is lost due to transmission line and in-house consumption. (author)

  5. Short-term electric power demand forecasting based on economic-electricity transmission model

    Science.gov (United States)

    Li, Wenfeng; Bai, Hongkun; Liu, Wei; Liu, Yongmin; Wang, Yubin Mao; Wang, Jiangbo; He, Dandan

    2018-04-01

    Short-term electricity demand forecasting is the basic work to ensure safe operation of the power system. In this paper, a practical economic electricity transmission model (EETM) is built. With the intelligent adaptive modeling capabilities of Prognoz Platform 7.2, the econometric model consists of three industrial added value and income levels is firstly built, the electricity demand transmission model is also built. By multiple regression, moving averages and seasonal decomposition, the problem of multiple correlations between variables is effectively overcome in EETM. The validity of EETM is proved by comparison with the actual value of Henan Province. Finally, EETM model is used to forecast the electricity consumption of the 1-4 quarter of 2018.

  6. Automatic demand response referred to electricity spot price. Demo description

    International Nuclear Information System (INIS)

    Grande, Ove S.; Livik, Klaus; Hals, Arne

    2006-05-01

    This report presents background, technical solution and results from a test project (Demo I) developed in the DRR Norway) project. Software and technology from two different vendors, APAS and Powel ASA, are used to demonstrate a scheme for Automatic Demand Response (ADR) referred to spot price level and a system for documentation of demand response and cost savings. Periods with shortage of energy supply and hardly any investments in new production capacity have turned focus towards the need for increased price elasticity on the demand side in the Nordic power market. The new technology for Automatic Meter Reading (AMR) and Remote Load Control (RLC) provides an opportunity to improve the direct market participation from the demand side by introducing automatic schemes that reduce the need for customer attention to hourly market prices. The low prioritized appliances, and not the total load, are in this report defined as the Demand Response Objects, based on the assumption that there is a limit for what the customers are willing to pay for different uses of electricity. Only disconnection of residential water heaters is included in the demo, due to practical limitations. The test was performed for a group of single family houses over a period of 2 months. All the houses were equipped with a radio controlled 'Ebox' unit attached to the water heater socket. The settlement and invoicing were based on hourly metered values (kWh/h), which means that the customer benefit is equivalent to the accumulated changes in the electricity cost per hour. The actual load reduction is documented by comparison between the real meter values for the period and a reference curve. The curves show significant response to the activated control in the morning hours. In the afternoon it is more difficult to register the response, probably due to 'disturbing' activities like cooking etc. Demo I shows that load reduction referred to spot price level can be done in a smooth way. The experiences

  7. Renewable Electricity Futures Study. Volume 3: End-Use Electricity Demand

    Energy Technology Data Exchange (ETDEWEB)

    Hostick, D.; Belzer, D.B.; Hadley, S.W.; Markel, T.; Marnay, C.; Kintner-Meyer, M.

    2012-06-01

    The Renewable Electricity Futures (RE Futures) Study investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. The analysis focused on the sufficiency of the geographically diverse U.S. renewable resources to meet electricity demand over future decades, the hourly operational characteristics of the U.S. grid with high levels of variable wind and solar generation, and the potential implications of deploying high levels of renewables in the future. RE Futures focused on technical aspects of high penetration of renewable electricity; it did not focus on how to achieve such a future through policy or other measures. Given the inherent uncertainties involved with analyzing alternative long-term energy futures as well as the multiple pathways that might be taken to achieve higher levels of renewable electricity supply, RE Futures explored a range of scenarios to investigate and compare the impacts of renewable electricity penetration levels (30%-90%), future technology performance improvements, potential constraints to renewable electricity development, and future electricity demand growth assumptions. RE Futures was led by the National Renewable Energy Laboratory (NREL) and the Massachusetts Institute of Technology (MIT).

  8. Renewable Electricity Futures Study. Volume 3. End-Use Electricity Demand

    Energy Technology Data Exchange (ETDEWEB)

    Hostick, Donna [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Belzer, David B. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Hadley, Stanton W. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Markel, Tony [National Renewable Energy Lab. (NREL), Golden, CO (United States); Marnay, Chris [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Kintner-Meyer, Michael [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2012-06-15

    The Renewable Electricity Futures (RE Futures) Study investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. The analysis focused on the sufficiency of the geographically diverse U.S. renewable resources to meet electricity demand over future decades, the hourly operational characteristics of the U.S. grid with high levels of variable wind and solar generation, and the potential implications of deploying high levels of renewables in the future. RE Futures focused on technical aspects of high penetration of renewable electricity; it did not focus on how to achieve such a future through policy or other measures. Given the inherent uncertainties involved with analyzing alternative long-term energy futures as well as the multiple pathways that might be taken to achieve higher levels of renewable electricity supply, RE Futures explored a range of scenarios to investigate and compare the impacts of renewable electricity penetration levels (30%–90%), future technology performance improvements, potential constraints to renewable electricity development, and future electricity demand growth assumptions. RE Futures was led by the National Renewable Energy Laboratory (NREL) and the Massachusetts Institute of Technology (MIT). Learn more at the RE Futures website. http://www.nrel.gov/analysis/re_futures/

  9. Accelerating residential PV expansion: demand analysis for competitive electricity markets

    International Nuclear Information System (INIS)

    Duke, Richard; Williams, Robert; Payne, Adam

    2005-01-01

    This article quantifies the potential market for grid-connected, residential photovoltaic (PV) electricity integrated into new homes built in the US. It complements an earlier supply-side analysis by the authors that demonstrates the potential to reduce PV module prices below $1.5/W p by scaling up existing thin-film technology in 100 MW p /yr manufacturing facilities. The present article demonstrates that, at that price, PV modules may be cost effective in 125,000 new home installations per year (0.5 GW p /yr). While this market is large enough to support multiple scaled up thin-film PV factories, inefficient energy pricing and demand-side market failures will inhibit prospective PV consumers without strong public policy support. Net metering rules, already implemented in many states to encourage PV market launch, represent a crude but reasonable surrogate for efficient electricity pricing mechanisms that may ultimately emerge to internalize the externality benefits of PV. These public benefits include reduced air pollution damages (estimated costs of damage to human health from fossil fuel power plants are presented in Appendix A), deferral of transmission and distribution capital expenditures, reduced exposure to fossil fuel price risks, and increased electricity system reliability for end users. Thus, net metering for PV ought to be implemented as broadly as possible and sustained until efficient pricing is in place. Complementary PV 'buydowns' (e.g., a renewable portfolio standard with a specific PV requirement) are needed to jumpstart regional PV markets

  10. Surging electricity demand growth bolsters outlook for natural gas

    International Nuclear Information System (INIS)

    Koen, A.D.

    1994-01-01

    Economic expansion and regulatory reform are combining to boost global opportunities for burning gas to generate electric power. Companies producing, marketing, or transporting gas are capitalizing on the improved outlook by seizing on synergistic roles in the power generation chain. Much of the improved outlook for gas stems from projected hearty increases in global demand for electricity. Bechtel Power Corp., estimates global power generation capacity during 1994--2003 will increase to as much as 1.2 billion kw, about 25% of which could be added by independent power production (IPPs). Since about 200 bcf of gas reserves producing about 20 MMcfd of gas is needed to fuel of a 100,000 kw electric generating station for 25 years, that adds up to a major growth opportunity for gas producers. The paper discusses the assessment of gas reserves, US power growth, the intent of the Energy Policy Act of 1992 (Epact), effects of Epact, gas industry response, power marketing units, synergistic possibilities, effects on US utilities, international power imperatives, non-US projects, funding good projects, and forecasting future developments

  11. Evolution of residential electricity demand by end-use in Quebec 1979-1989: A conditional demand analysis

    International Nuclear Information System (INIS)

    Lafrance, G.; Perron, D.

    1994-01-01

    Some of the main conclusions are presented from a temporal analysis of three large-scale electricity demand surveys (1979, 1984, and 1989) for the Quebec residential sector. A regression method called conditional demand analysis was used. The study allows a number of conclusions about certain electricity consumption trends by end-uses from 1979 to 1989 by household type and by vintage category. For example, the results indicate that decreasing electricity consumption between 1979 and 1984 for a typical dwelling equipped with electric space heating was mainly related to a large decline in net heating consumption. Overall, the results suggest that some permanent energy savings have been realized by a typical household equipped with an electric heating system due to improvements in standards and changes in customer behavior. These energy savings were partly offset by increased electricity consumption from the purchase of new appliances and an increase in the demand for hot water. 7 refs., 1 fig., 8 tabs

  12. Electricity demand of manufacturing sector in Turkey. A translog cost approach

    International Nuclear Information System (INIS)

    Boeluek, Guelden; Koc, A. Ali

    2010-01-01

    This paper models factor demand for manufacturing sector in Turkey. We estimated a translog cost function with four factor consist of capital, labor, intermediate input and electricity over the 1980-2001. Our objective, taking in the consideration electricity as production input, was twofold: on the one hand, to estimate the price elasticity of electricity demand in manufacturing sector, and on the other hand to use cross-price and Morishima Elasticities of Substitution results for structural analysis regarding effects of electricity liberalization which initiated in 2001. Empirical result shows that electricity demand is relatively price sensitive (- 0.85). Our result in terms of electricity price is consistent with the previous studies. While electricity-labor and electricity-capital inputs are complementary, results indicate the existence of substitution possibilities between electricity and intermediate input. This means that changes in electricity prices have impact on labor demand and investment demand. These results have important implications for public policy. (author)

  13. Electricity demand of manufacturing sector in Turkey. A translog cost approach

    Energy Technology Data Exchange (ETDEWEB)

    Boeluek, Guelden; Koc, A. Ali [Akdeniz University, Department of Economics, Antalya, 07058 (Turkey)

    2010-05-15

    This paper models factor demand for manufacturing sector in Turkey. We estimated a translog cost function with four factor consist of capital, labor, intermediate input and electricity over the 1980-2001. Our objective, taking in the consideration electricity as production input, was twofold: on the one hand, to estimate the price elasticity of electricity demand in manufacturing sector, and on the other hand to use cross-price and Morishima Elasticities of Substitution results for structural analysis regarding effects of electricity liberalization which initiated in 2001. Empirical result shows that electricity demand is relatively price sensitive (- 0.85). Our result in terms of electricity price is consistent with the previous studies. While electricity-labor and electricity-capital inputs are complementary, results indicate the existence of substitution possibilities between electricity and intermediate input. This means that changes in electricity prices have impact on labor demand and investment demand. These results have important implications for public policy. (author)

  14. Latin American electric power developments and hydrocarbon demands

    International Nuclear Information System (INIS)

    Sierra, G.S.

    1994-01-01

    Energy sectors in Latin American countries are undergoing a series of far-reaching changes in institutional arrangements and roles. These changes will have a decisive influence on energy sector evolution in coming decades. The results of two decades of mismanagement in the region's energy sector are outlined, showing stagnation in the electric power and petroleum industries caused by such factors as bureaucratic management, preferential treatment given to public enterprises, the adoption of objectives other than economic profitability, insufficient self-generation of resources due to tariffs not reflecting economic costs, and heavy debt burdens. If forecasts of future energy demand in Latin America are correct, the region's hydrocarbon sector will have to invest ca US$20 billion/y and the electric power sector nearly the same amount. This is considered beyond the capacity of the region's industries. Private sector participation is expected to raise the efficiency level of the hydrocarbon and power industries through such initiatives as privatization (complete or partial), joint government-private ventures, subcontracting, direct investment, and opening of monopolies such as power distribution to third-party competition. The state role in this process will be to create a suitable environment for private enterprise including clear and stable rules and regulatory frameworks. Financing options are discussed along with ways to reduce investment requirements. It is especially possible to reduce such requirements in the power sector through such means as retrofitting of plants with more modern equipment, reducing power losses, improved metering and billing, energy substitution, demand-side management, and energy conservation programs

  15. Demand response in U.S. electricity markets: Empirical evidence

    International Nuclear Information System (INIS)

    Cappers, Peter; Goldman, Charles; Kathan, David

    2010-01-01

    Empirical evidence concerning demand response (DR) resources is needed in order to establish baseline conditions, develop standardized methods to assess DR availability and performance, and to build confidence among policymakers, utilities, system operators, and stakeholders that DR resources do offer a viable, cost-effective alternative to supply-side investments. This paper summarizes the existing contribution of DR resources in U.S. electric power markets. In 2008, customers enrolled in existing wholesale and retail DR programs were capable of providing ∝38,000 MW of potential peak load reductions in the United States. Participants in organized wholesale market DR programs, though, have historically overestimated their likely performance during declared curtailments events, but appear to be getting better as they and their agents gain experience. In places with less developed organized wholesale market DR programs, utilities are learning how to create more flexible DR resources by adapting legacy load management programs to fit into existing wholesale market constructs. Overall, the development of open and organized wholesale markets coupled with direct policy support by the Federal Energy Regulatory Commission has facilitated new entry by curtailment service providers, which has likely expanded the demand response industry and led to product and service innovation. (author)

  16. Impact of peak electricity demand in distribution grids: a stress test

    NARCIS (Netherlands)

    Hoogsteen, Gerwin; Molderink, Albert; Hurink, Johann L.; Smit, Gerardus Johannes Maria; Schuring, Friso; Kootstra, Ben

    2015-01-01

    The number of (hybrid) electric vehicles is growing, leading to a higher demand for electricity in distribution grids. To investigate the effects of the expected peak demand on distribution grids, a stress test with 15 electric vehicles in a single street is conducted and described in this paper.

  17. Maximum on the electrical conductivity polytherm of molten TeCl{sub 4}

    Energy Technology Data Exchange (ETDEWEB)

    Salyulev, Alexander B.; Potapov, Alexei M. [Russian Academy of Sciences, Ekaterinburg (Russian Federation). Inst. of High-Temperature Electrochemistry

    2017-09-01

    The electrical conductivity of molten TeCl{sub 4} was measured up to 761 K, i.e. 106 degrees above the normal boiling point of the salt. For the first time it was found that TeCl{sub 4} electrical conductivity polytherm has a maximum. It was recorded at 705 K (Κ{sub max}=0.245 Sm/cm), whereupon the conductivity decreases as the temperature rises. The activation energy of electrical conductivity was calculated.

  18. Maximum on the electrical conductivity polytherm of molten TeCl4

    International Nuclear Information System (INIS)

    Salyulev, Alexander B.; Potapov, Alexei M.

    2017-01-01

    The electrical conductivity of molten TeCl 4 was measured up to 761 K, i.e. 106 degrees above the normal boiling point of the salt. For the first time it was found that TeCl 4 electrical conductivity polytherm has a maximum. It was recorded at 705 K (Κ max =0.245 Sm/cm), whereupon the conductivity decreases as the temperature rises. The activation energy of electrical conductivity was calculated.

  19. Estimating Water Demand in Urban Indonesia: A Maximum Likelihood Approach to block Rate Pricing Data

    NARCIS (Netherlands)

    Rietveld, Piet; Rouwendal, Jan; Zwart, Bert

    1997-01-01

    In this paper the Burtless and Hausman model is used to estimate water demand in Salatiga, Indonesia. Other statistical models, as OLS and IV, are found to be inappropiate. A topic, which does not seem to appear in previous studies, is the fact that the density function of the loglikelihood can be

  20. Evaluation of the electric vehicle impact in the power demand curve in a smart grid environment

    International Nuclear Information System (INIS)

    Morais, Hugo; Sousa, Tiago; Vale, Zita; Faria, Pedro

    2014-01-01

    Highlights: • Multi-objective optimization of operation costs and load factor. • Contribution of electric vehicles to load diagram leveling. • Use of epigraph variables to transform non-convex functions in convex ones. • Evaluation of the obtained results considering different EVs penetration. - Abstract: Smart grids with an intensive penetration of distributed energy resources will play an important role in future power system scenarios. The intermittent nature of renewable energy sources brings new challenges, requiring an efficient management of those sources. Additional storage resources can be beneficially used to address this problem; the massive use of electric vehicles, particularly of vehicle-to-grid (usually referred as gridable vehicles or V2G), becomes a very relevant issue. This paper addresses the impact of Electric Vehicles (EVs) in system operation costs and in power demand curve for a distribution network with large penetration of Distributed Generation (DG) units. An efficient management methodology for EVs charging and discharging is proposed, considering a multi-objective optimization problem. The main goals of the proposed methodology are: to minimize the system operation costs and to minimize the difference between the minimum and maximum system demand (leveling the power demand curve). The proposed methodology perform the day-ahead scheduling of distributed energy resources in a distribution network with high penetration of DG and a large number of electric vehicles. It is used a 32-bus distribution network in the case study section considering different scenarios of EVs penetration to analyze their impact in the network and in the other energy resources management

  1. Air pollution, nuclear power and electricity demand: an economic perspective

    International Nuclear Information System (INIS)

    Chapman, D.; Mount, T.; Czerwinski, M.; Younger, M.

    1983-09-01

    We have studied the potential for physical or financial disruption of the electric utility system in New York as it may be affected by nuclear power availability, air pollution control policy, inflation, and economic growth. The method of analysis is the EPA-sponsored CCMU model which integrates utility economics, demand forecasting and customer charges, air pollution control, and power plant dispatching. The CCMU model is a partial version of the AUSM; the latter model is being developed to include coal supply and capacity planning. Of all the cases examined, only one type seems to create a severe crisis which leads to possible public reorganization of the industry. These are the cases in which the Shoreham and Nine Mile 2 plants are not operated, and 50% or more of the investment cost is not allowed in the rate base. In these circumstances, the state's utilities would apparently be unable to meet debt obligations and would also need to discontinue dividend payments. The extremity of this situation should be emphasized. These specific cases already assume that liability for debt and dividend payments has been shared equally over all of the state's utilities and customers. It assumes that the state's Power Pool has already implemented a plan by which the principal owners of the two plants are relieved of their principal financial and generating responsibilities. In all other cases studied, the statewide industry appears capable of managing the problems examined

  2. Which electricity market design to encourage the development of demand response?

    OpenAIRE

    Vincent Rious, Fabien Roques and Yannick Perez

    2012-01-01

    Demand response is a cornerstone problem in electricity markets under climate change constraint. Most liberalized electricity markets have a poor track record at encouraging the deployment of smart meters and the development of demand response. In Europe, different models are considered for demand response, from a development under a regulated regime to a development under competitive perspectives. In this paper, focusing on demand response and smart metering for mid-size and small consumers,...

  3. Which electricity market design to encourage the development of demand response?

    OpenAIRE

    Rious , Vincent; Perez , Yannick; Roques , Fabien

    2015-01-01

    International audience; Demand response is a cornerstone problem in electricity markets under climate change constraints. Most liberalized electricity markets have a poor track record at encouraging the deployment of smart meters and the development of demand response. In Europe, different models are considered for demand response, from a development under a regulated regime to a development under competitive perspectives. In this paper focusing on demand response and smart metering for mid-­...

  4. Aggregate demand for electricity in South Africa: An analysis using the bounds testing approach to cointegration

    International Nuclear Information System (INIS)

    Amusa, Hammed; Amusa, Kafayat; Mabugu, Ramos

    2009-01-01

    Electricity demand in South Africa has grown at a very rapid rate over the past decade. As part of reform initiatives to enhance long-term sustainability of the country's electricity industry, South Africa's authorities have in recent years sought to develop an electricity pricing framework that is cost reflective and forms the cornerstone of demand management schemes meant to foster changes in consumption behaviour and enhance efficiency in resource use. The effects of any pricing policy on aggregate electricity consumption will depend on a useful understanding of the factors that influence electricity demand, and the magnitude to which electricity demand responds to changes in such factors. In this context, this paper applies the bounds testing approach to cointegration within an autoregressive distributed lag framework to examine the aggregate demand for electricity in South Africa during the period 1960-2007. The results indicate that in the long run, income is the main determinant of electricity demand. With electricity prices having an insignificant effect on aggregate electricity demand, future pricing policies will need to ensure that electricity prices are cost reflective and enhance efficiency of electricity supply and use.

  5. Aggregate demand for electricity in South Africa: An analysis using the bounds testing approach to cointegration

    Energy Technology Data Exchange (ETDEWEB)

    Amusa, Hammed; Mabugu, Ramos [Financial and Fiscal Commission, Private Bag X69, Halfway Gardens, 1685 Midrand (South Africa); Amusa, Kafayat [Department of Economics, University of South Africa, P.O. Box 392, UNISA 0003 (South Africa)

    2009-10-15

    Electricity demand in South Africa has grown at a very rapid rate over the past decade. As part of reform initiatives to enhance long-term sustainability of the country's electricity industry, South Africa's authorities have in recent years sought to develop an electricity pricing framework that is cost reflective and forms the cornerstone of demand management schemes meant to foster changes in consumption behaviour and enhance efficiency in resource use. The effects of any pricing policy on aggregate electricity consumption will depend on a useful understanding of the factors that influence electricity demand, and the magnitude to which electricity demand responds to changes in such factors. In this context, this paper applies the bounds testing approach to cointegration within an autoregressive distributed lag framework to examine the aggregate demand for electricity in South Africa during the period 1960-2007. The results indicate that in the long run, income is the main determinant of electricity demand. With electricity prices having an insignificant effect on aggregate electricity demand, future pricing policies will need to ensure that electricity prices are cost reflective and enhance efficiency of electricity supply and use. (author)

  6. Analysis and design of a Taguchi-Grey based electricity demand predictor for energy management systems

    International Nuclear Information System (INIS)

    Yao, Albert W.L.; Chi, S.C.

    2004-01-01

    In order to use electricity efficiently, a demand control management system is one of the effective ways to reduce energy consumption and electric bills. An electricity demand control system is used as a means to monitor and manage the usage of electricity effectively. Moreover, it is a useful tool for avoiding penalties beyond the contracted demand value of electricity with the electric power company. In this project, we developed a Taguchi-Grey based predictor to forecast the demand value of electricity on line. In a Grey prediction, the parameter settings are highly relevant to the accuracy of forecasting. A Taguchi method was employed to optimize the parameter settings for the Grey based electricity demand value predictor. Our experimental results show that the optimal parameter settings of the Grey prediction are α=0.4, five point modeling and three minute sampling time of the data acquisition system. The improved Taguchi-Grey based electricity demand predictor in conjunction with the PC based electricity demand control system is a cost effective and efficient means to manage the usage of electricity

  7. Benefits and challenges of electrical demand response: A critical review

    DEFF Research Database (Denmark)

    O'Connell, Niamh; Pinson, Pierre; Madsen, Henrik

    2014-01-01

    and challenges of demand response. These benefits include the ability to balance fluctuations in renewable generation and consequently facilitate higher penetrations of renewable resources on the power system, an increase in economic efficiency through the implementation of real-time pricing, and a reduction...... in generation capacity requirements. Nevertheless, demand response is not without its challenges. The key challenges for demand response centre around establishing reliable control strategies and market frameworks so that the demand response resource can be used optimally. One of the greatest challenges...... for demand response is the lack of experience, and the consequent need to employ extensive assumptions when modelling and evaluating this resource. This paper concludes with an examination of these assumptions, which range from assuming a fixed linear price–demand relationship for price responsive demand...

  8. Prospective Life Cycle Assessment of the Increased Electricity Demand Associated with the Penetration of Electric Vehicles in Spain

    OpenAIRE

    Zaira Navas-Anguita; Diego García-Gusano; Diego Iribarren

    2018-01-01

    The penetration of electric vehicles (EV) seems to be a forthcoming reality in the transport sector worldwide, involving significant increases in electricity demand. However, many countries such as Spain have not yet set binding policy targets in this regard. When compared to a business-as-usual situation, this work evaluates the life-cycle consequences of the increased electricity demand of the Spanish road transport technology mix until 2050. This is done by combining Life Cycle Assessment ...

  9. Demand Response in Europe's Electricity Sector: Market barriers and outstanding issues

    International Nuclear Information System (INIS)

    Eid, Cherrelle

    2015-01-01

    In October 2014, Europe's drive for sustainability has been further continued with the set objectives for 2030, aiming for 40% emission reduction compared to 1990 levels and at least a 27% share of renewable energy sources. For the longer term, the European Commission (EC) targets a zero CO_2 emitting electricity sector in 2050. Those objectives for the electricity sector have a large impact on the expected development of electricity generation, but also on the evolution of demand. To meet those objectives, a larger share of electricity supply will come from intermittent sources like wind turbines and solar panels. In an electric system that is largely based on renewable electricity sources, it is desired to have higher electricity consumption in moments when more renewable electricity is being produced, and a lower consumption in times of lower renewable production. Demand response is related to the adaptability of the electricity demand to the availability of supply. The development of demand response is rooted in the need for carbon emission reductions and for efficient use of installed generation capacities with the growth of power consumption. In addition to providing flexibility to the electric system, demand response could be a direct source of revenue to households and businesses. In 2013, in the United States, businesses and homeowners earned over $2.2 billion in revenues from demand response together with other avoided investment in grid infrastructure and power plants. This source of direct revenue could also be made available in Europe and would release financial benefits to local economies (SEDC, 2014). The reliability improvements as well as the economic and sustainability potential coming from a more responsive electricity demand are fully acknowledged. However, demand response is still immaturely developed in Europe. If Europe wants to make a step forward to a more sustainable electricity sector, the development of demand response is an inevitable

  10. Climate change and peak demand for electricity: Evaluating policies for reducing peak demand under different climate change scenarios

    Science.gov (United States)

    Anthony, Abigail Walker

    This research focuses on the relative advantages and disadvantages of using price-based and quantity-based controls for electricity markets. It also presents a detailed analysis of one specific approach to quantity based controls: the SmartAC program implemented in Stockton, California. Finally, the research forecasts electricity demand under various climate scenarios, and estimates potential cost savings that could result from a direct quantity control program over the next 50 years in each scenario. The traditional approach to dealing with the problem of peak demand for electricity is to invest in a large stock of excess capital that is rarely used, thereby greatly increasing production costs. Because this approach has proved so expensive, there has been a focus on identifying alternative approaches for dealing with peak demand problems. This research focuses on two approaches: price based approaches, such as real time pricing, and quantity based approaches, whereby the utility directly controls at least some elements of electricity used by consumers. This research suggests that well-designed policies for reducing peak demand might include both price and quantity controls. In theory, sufficiently high peak prices occurring during periods of peak demand and/or low supply can cause the quantity of electricity demanded to decline until demand is in balance with system capacity, potentially reducing the total amount of generation capacity needed to meet demand and helping meet electricity demand at the lowest cost. However, consumers need to be well informed about real-time prices for the pricing strategy to work as well as theory suggests. While this might be an appropriate assumption for large industrial and commercial users who have potentially large economic incentives, there is not yet enough research on whether households will fully understand and respond to real-time prices. Thus, while real-time pricing can be an effective tool for addressing the peak load

  11. A novel machine learning approach for estimation of electricity demand: An empirical evidence from Thailand

    International Nuclear Information System (INIS)

    Mostafavi, Elham Sadat; Mostafavi, Seyyed Iman; Jaafari, Arefeh; Hosseinpour, Fariba

    2013-01-01

    Highlights: • A hybrid approach is presented for the estimation of the electricity demand. • The proposed method integrates the capabilities of GP and SA. • The GSA model makes accurate predictions of the electricity demand. - Abstract: This study proposes an innovative hybrid approach for the estimation of the long-term electricity demand. A new prediction equation was developed for the electricity demand using an integrated search method of genetic programming and simulated annealing, called GSA. The annual electricity demand was formulated in terms of population, gross domestic product (GDP), stock index, and total revenue from exporting industrial products of the same year. A comprehensive database containing total electricity demand in Thailand from 1986 to 2009 was used to develop the model. The generalization of the model was verified using a separate testing data. A sensitivity analysis was conducted to investigate the contribution of the parameters affecting the electricity demand. The GSA model provides accurate predictions of the electricity demand. Furthermore, the proposed model outperforms a regression and artificial neural network-based models

  12. Electricity demand profile with high penetration of heat pumps in Nordic area

    DEFF Research Database (Denmark)

    Liu, Zhaoxi; Wu, Qiuwei; Nielsen, Arne Hejde

    2013-01-01

    This paper presents the heat pump (HP) demand profile with high HP penetration in the Nordic area in order to achieve the carbon neutrality power system. The calculation method in the European Standard EN14825 was used to estimate the HP electricity demand profile. The study results show...... there will be high power demand from HPs and the selection of supplemental heating for heat pumps has a big impact on the peak electrical power load of heating. The study in this paper gives an estimate of the scale of the electricity demand with high penetration of heat pumps in the Nordic area....

  13. Modelling aggregate domestic electricity demand in Ghana: An autoregressive distributed lag bounds cointegration approach

    International Nuclear Information System (INIS)

    Adom, Philip Kofi; Bekoe, William; Akoena, Sesi Kutri Komla

    2012-01-01

    In spite of the varying supply boosting efforts made by various governments to deal with the existing demand–supply gap in the electricity sector, the incessant growth in aggregate domestic electricity demand has made these efforts futile. As an objective, this paper attempts to identify the factors responsible for the historical growth trends in aggregate domestic electricity demand quantifying their effects both in the short-run and long-run periods using the ARDL Bounds cointegration approach and the sample period 1975 to 2005. In the long-run, real per capita GDP, industry efficiency, structural changes in the economy, and degree of urbanisation are identified as the main driving force behind the historical growth trend in aggregate domestic electricity demand. However, in the short-run, real per capita GDP, industry efficiency, and degree of urbanisation are the main drivers of aggregate domestic electricity demand. Industry efficiency is the only factor that drives aggregate domestic electricity demand downwards. However, the negative efficiency effect is insufficient to have outweighed the positive income, output, and demographic effects, hence the continual growth in aggregate domestic electricity demand. As a policy option, we recommend that appropriate electricity efficiency standards be implemented at the industry level. - Highlights: ► Real per capita GDP is the primary determinant of electricity demand both in the short and long-run. ► Industrial efficiency, structural changes and urbanisation rate play secondary role. ► The positive income, output, and demographic effects outweigh the negative efficiency effects.

  14. The role of price elastic demand in market power in the Nordic electricity markets

    International Nuclear Information System (INIS)

    Ravn, H.F.

    2004-01-01

    The paper discusses the modelling and analysis of market power and price elastic demand in the Nordic electricity spot market, Nordpool. The modelling of market power in the electricity sector must take into account a number of features that are specific to the electricity sector. First, electricity cannot be stored, but must be produced simultaneously with consumption. This aspect is, however, modified by the possibility of using hydro reservoirs as an indirect electricity storage. Second, the electricity transmission network plays an important role by breaking the market into several geographically separate sub-markets with different prices. Moreover, the specific bottlenecks may differ from hour to hour, according to the balance between supply and demand in each sub-market. Third, the demand side is presently characterised by very limited experience with hour to-hour-changes in electricity prices and very limited experience with short time adjustments of electricity consumption in response to changes in the electricity price. In the present paper three basic models for supply side competition on the Nordpool spot market will be presented, viz., perfect competition, Cournot competition and Supply Function Equilibrium. The models represent price and quantity settlement, including determination of price areas (bottle necks), in accordance with the way the Nordpool market functions. The models will incorporate electricity demand which is responsive to the electricity price. The paper describes the role of demand response for the determination of the electricity prices in each of the three supply side competition models. (au)

  15. Assessment of precast beam-column using capacity demand response spectrum subject to design basis earthquake and maximum considered earthquake

    Science.gov (United States)

    Ghani, Kay Dora Abd.; Tukiar, Mohd Azuan; Hamid, Nor Hayati Abdul

    2017-08-01

    Malaysia is surrounded by the tectonic feature of the Sumatera area which consists of two seismically active inter-plate boundaries, namely the Indo-Australian and the Eurasian Plates on the west and the Philippine Plates on the east. Hence, Malaysia experiences tremors from far distant earthquake occurring in Banda Aceh, Nias Island, Padang and other parts of Sumatera Indonesia. In order to predict the safety of precast buildings in Malaysia under near field ground motion the response spectrum analysis could be used for dealing with future earthquake whose specific nature is unknown. This paper aimed to develop of capacity demand response spectrum subject to Design Basis Earthquake (DBE) and Maximum Considered Earthquake (MCE) in order to assess the performance of precast beam column joint. From the capacity-demand response spectrum analysis, it can be concluded that the precast beam-column joints would not survive when subjected to earthquake excitation with surface-wave magnitude, Mw, of more than 5.5 Scale Richter (Type 1 spectra). This means that the beam-column joint which was designed using the current code of practice (BS8110) would be severely damaged when subjected to high earthquake excitation. The capacity-demand response spectrum analysis also shows that the precast beam-column joints in the prototype studied would be severely damaged when subjected to Maximum Considered Earthquake (MCE) with PGA=0.22g having a surface-wave magnitude of more than 5.5 Scale Richter, or Type 1 spectra.

  16. Assessment of demand for natural gas from the electricity sector in India

    DEFF Research Database (Denmark)

    Shukla, P.R.; Dhar, Subash; Victor, David G.

    2009-01-01

    Electricity sector is among the key users of natural gas. The sustained electricity deficit and environment policies have added to an already rising demand for gas. This paper tries to understand gas demand in future from electricity sector. This paper models the future demand for gas in India from...... the electricity sector under alternative scenarios for the period 2005–2025, using bottom-up ANSWER MARKAL model. The scenarios are differentiated by alternate economic growth projections and policies related to coal reforms, infrastructure choices and local environment. The results across scenarios show that gas...... competes with coal as a base-load option if price difference is below US $ 4 per MBtu. At higher price difference gas penetrates only the peak power market. Gas demand is lower in the high economic growth scenario, since electricity sector is more flexible in substitution of primary energy. Gas demand...

  17. A demand/supply and price outlook for electricity in Ontario

    International Nuclear Information System (INIS)

    Dalton, J.

    2004-01-01

    This paper presents the demand/supply and price outlook for electricity in Ontario. The paper examines the near term outlook, critical demand and supply issues, the projected Ontario demand/supply balances and finally concludes by looking at the challenges for Ontario's new market structure

  18. Electricity demand in France: what's at stake for the energy transition?

    International Nuclear Information System (INIS)

    Berghmans, Nicolas

    2017-02-01

    This study identifies five key issues linked to electricity consumption to be taken into consideration in the management of the French power system transition: articulating the building stock renovation strategy and electricity consumption; integrating demand for electricity stemming from the development of electric vehicles; addressing winter 'peak' demand with specific demand-side policies; establishing energy demand management economic models as a flexible solution for the power system; identifying the impact of the emergence of a power system that is decentralised, balanced locally and connected with other energy carriers on the nature of demand for power from the grid. In the context of weak economic and demographic growth, the recent stabilization of electricity demand in France can be attributed to 'structural' factors, i.e. the continued expansion of the tertiary sector in the economy and the acceleration in energy efficiency gains. This evolution was poorly anticipated by stakeholders in the sector, which contributed to an imbalance between electricity demand and supply in Europe. In the absence of a major disruption, planning for transition in the electrical system should be made assuming relatively stable demand. However, major transformations will change the nature of the requirements placed on the electricity system: the times at which energy is consumed, the ability to manage the demand side of the system, and the geographical location of electricity demand within the network. Five key challenges are identified to anticipate the development of electricity consumption patterns: the role of electricity in satisfying building sector heating requirements, the integration of electric vehicle charging, the evolution of the winter demand peak, the development of demand-side management, and the emergence of an electric system based on local-level balancing. Too often considered an exogenous factor, the development in electricity consumption is in fact central

  19. Two-stage stochastic programming model for the regional-scale electricity planning under demand uncertainty

    International Nuclear Information System (INIS)

    Huang, Yun-Hsun; Wu, Jung-Hua; Hsu, Yu-Ju

    2016-01-01

    Traditional electricity supply planning models regard the electricity demand as a deterministic parameter and require the total power output to satisfy the aggregate electricity demand. But in today's world, the electric system planners are facing tremendously complex environments full of uncertainties, where electricity demand is a key source of uncertainty. In addition, electricity demand patterns are considerably different for different regions. This paper developed a multi-region optimization model based on two-stage stochastic programming framework to incorporate the demand uncertainty. Furthermore, the decision tree method and Monte Carlo simulation approach are integrated into the model to simplify electricity demands in the form of nodes and determine the values and probabilities. The proposed model was successfully applied to a real case study (i.e. Taiwan's electricity sector) to show its applicability. Detail simulation results were presented and compared with those generated by a deterministic model. Finally, the long-term electricity development roadmap at a regional level could be provided on the basis of our simulation results. - Highlights: • A multi-region, two-stage stochastic programming model has been developed. • The decision tree and Monte Carlo simulation are integrated into the framework. • Taiwan's electricity sector is used to illustrate the applicability of the model. • The results under deterministic and stochastic cases are shown for comparison. • Optimal portfolios of regional generation technologies can be identified.

  20. Power plant site evaluation, electric energy demand forecasts - Douglas Point Site. Volume 3. Final report

    International Nuclear Information System (INIS)

    Wilson, J.W.

    1975-07-01

    This is part of a series of reports containing an evaluation of the proposed Douglas Point nuclear generating station site located on the Potomac River in Maryland 30 miles south of Washington, D.C. This report contains chapters on the Potomac Electric Power Company's market, forecasting future demand, modelling, a residential demand model, a nonresidential demand model, the Southern Maryland Electric Cooperative Model, short term predictive accuracy, and total system requirements

  1. Economic information from Smart Meter: Nexus Between Demand Profile and Electricity Retail Price Between Demand Profile and Electricity Retail Price

    OpenAIRE

    Yu, Yang; Liu, Guangyi; Zhu, Wendong; Wang, Fei; Shu, Bin; Zhang, Kai; Rajagopal, Ram; Astier, Nicolas

    2016-01-01

    In this paper, we demonstrate that a consumer's marginal system impact is only determined by their demand profile rather than their demand level. Demand profile clustering is identical to cluster consumers according to their marginal impacts on system costs. A profile-based uniform-rate price is economically efficient as real-time pricing. We develop a criteria system to evaluate the economic efficiency of an implemented retail price scheme in a distribution system by comparing profile cluste...

  2. Generation Adequacy Report on the electricity supply-demand balance in France - 2011 Edition

    International Nuclear Information System (INIS)

    2012-01-01

    Working under the aegis of public authorities, RTE periodically prepares and makes public a multi-annual forecast of the electricity supply-demand balance in France, as required by law. The purpose of this report is to evaluate the ability of the French power system, in interaction with neighbouring systems, to properly satisfy demand, based on the likeliest scenarios for trends in demand, demand response and generation

  3. Letter to the Editor: Electric Vehicle Demand Model for Load Flow Studies

    DEFF Research Database (Denmark)

    Garcia-Valle, Rodrigo; Vlachogiannis, Ioannis (John)

    2009-01-01

    This paper introduces specific and simple model for electric vehicles suitable for load flow studies. The electric vehicles demand system is modelled as PQ bus with stochastic characteristics based on the concept of queuing theory. All appropriate variables of stochastic PQ buses are given...... with closed formulae as a function of charging time. Specific manufacturer model of electric vehicles is used as study case....

  4. Income and price elasticities of electricity demand: Aggregate and sector-wise analyses

    International Nuclear Information System (INIS)

    Jamil, Faisal; Ahmad, Eatzaz

    2011-01-01

    Cointegration and vector error correction modeling approaches are widely used in electricity demand analysis. The study rigorously examines the determinants of electricity demand at aggregate and sectoral levels in Pakistan. In the backdrop of severe electricity shortages, our empirical findings give support to the existence of a stable long-run relationship among the variables and indicate that electricity demand is elastic in the long run to both income and price at aggregate level. At sectoral level, long-run income and price elasticity estimates follow this pattern except in agricultural sector, where electricity demand is found elastic to output but inelastic to electricity price. On the contrary, the coefficients for income and price are rather small and mostly insignificant in the short run. We employed temperature index, price of diesel oil and capital stock at aggregate and sectoral levels as exogenous variables. These variables account for most of the variations in electricity demand in the short run. It shows that mechanization of the economy significantly affect the electricity demand at macro level. Moreover, elastic electricity demand with respect to electricity price in most of the sectors implies that electricity price as a policy tool can be used for efficient use and conservation. - Highlights: → The study conducts analysis for aggregate and four sectors. → Sectoral analyses are for residential, commercial, manufacturing and agricultural sectors. → We obtained higher positive income and negative price elasticity in the long run. → The higher price elasticity implies that price can be used as a policy tool. → Capital stock and temperature variables explain most of the short-run demand fluctuations.

  5. Income and price elasticities of electricity demand: Aggregate and sector-wise analyses

    Energy Technology Data Exchange (ETDEWEB)

    Jamil, Faisal, E-mail: fsljml@hotmail.com [School of Economics, Quaid-e-Azam University, Islamabad (Pakistan); Ahmad, Eatzaz, E-mail: eatzaz@qau.edu.pk [School of Economics, Quaid-e-Azam University, Islamabad (Pakistan)

    2011-09-15

    Cointegration and vector error correction modeling approaches are widely used in electricity demand analysis. The study rigorously examines the determinants of electricity demand at aggregate and sectoral levels in Pakistan. In the backdrop of severe electricity shortages, our empirical findings give support to the existence of a stable long-run relationship among the variables and indicate that electricity demand is elastic in the long run to both income and price at aggregate level. At sectoral level, long-run income and price elasticity estimates follow this pattern except in agricultural sector, where electricity demand is found elastic to output but inelastic to electricity price. On the contrary, the coefficients for income and price are rather small and mostly insignificant in the short run. We employed temperature index, price of diesel oil and capital stock at aggregate and sectoral levels as exogenous variables. These variables account for most of the variations in electricity demand in the short run. It shows that mechanization of the economy significantly affect the electricity demand at macro level. Moreover, elastic electricity demand with respect to electricity price in most of the sectors implies that electricity price as a policy tool can be used for efficient use and conservation. - Highlights: > The study conducts analysis for aggregate and four sectors. > Sectoral analyses are for residential, commercial, manufacturing and agricultural sectors. > We obtained higher positive income and negative price elasticity in the long run. > The higher price elasticity implies that price can be used as a policy tool. > Capital stock and temperature variables explain most of the short-run demand fluctuations.

  6. Electricity Consumption Forecasting Scheme via Improved LSSVM with Maximum Correntropy Criterion

    Directory of Open Access Journals (Sweden)

    Jiandong Duan

    2018-02-01

    Full Text Available In recent years, with the deepening of China’s electricity sales side reform and electricity market opening up gradually, the forecasting of electricity consumption (FoEC becomes an extremely important technique for the electricity market. At present, how to forecast the electricity accurately and make an evaluation of results scientifically are still key research topics. In this paper, we propose a novel prediction scheme based on the least-square support vector machine (LSSVM model with a maximum correntropy criterion (MCC to forecast the electricity consumption (EC. Firstly, the electricity characteristics of various industries are analyzed to determine the factors that mainly affect the changes in electricity, such as the gross domestic product (GDP, temperature, and so on. Secondly, according to the statistics of the status quo of the small sample data, the LSSVM model is employed as the prediction model. In order to optimize the parameters of the LSSVM model, we further use the local similarity function MCC as the evaluation criterion. Thirdly, we employ the K-fold cross-validation and grid searching methods to improve the learning ability. In the experiments, we have used the EC data of Shaanxi Province in China to evaluate the proposed prediction scheme, and the results show that the proposed prediction scheme outperforms the method based on the traditional LSSVM model.

  7. Impact of Uncoordinated Plug-in Electric Vehicle Charging on Residential Power Demand

    Energy Technology Data Exchange (ETDEWEB)

    Muratori, Matteo [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2018-01-22

    Electrification of transport offers opportunities to increase energy security, reduce carbon emissions, and improve local air quality. Plug-in electric vehicles (PEVs) are creating new connections between the transportation and electric sectors, and PEV charging will create opportunities and challenges in a system of growing complexity. Here, I use highly resolved models of residential power demand and PEV use to assess the impact of uncoordinated in-home PEV charging on residential power demand. While the increase in aggregate demand might be minimal even for high levels of PEV adoption, uncoordinated PEV charging could significantly change the shape of the aggregate residential demand, with impacts for electricity infrastructure, even at low adoption levels. Clustering effects in vehicle adoption at the local level might lead to high PEV concentrations even if overall adoption remains low, significantly increasing peak demand and requiring upgrades to the electricity distribution infrastructure. This effect is exacerbated when adopting higher in-home power charging.

  8. Impact of uncoordinated plug-in electric vehicle charging on residential power demand

    Science.gov (United States)

    Muratori, Matteo

    2018-03-01

    Electrification of transport offers opportunities to increase energy security, reduce carbon emissions, and improve local air quality. Plug-in electric vehicles (PEVs) are creating new connections between the transportation and electric sectors, and PEV charging will create opportunities and challenges in a system of growing complexity. Here, I use highly resolved models of residential power demand and PEV use to assess the impact of uncoordinated in-home PEV charging on residential power demand. While the increase in aggregate demand might be minimal even for high levels of PEV adoption, uncoordinated PEV charging could significantly change the shape of the aggregate residential demand, with impacts for electricity infrastructure, even at low adoption levels. Clustering effects in vehicle adoption at the local level might lead to high PEV concentrations even if overall adoption remains low, significantly increasing peak demand and requiring upgrades to the electricity distribution infrastructure. This effect is exacerbated when adopting higher in-home power charging.

  9. [Demography perspectives and forecasts of the demand for electricity].

    Science.gov (United States)

    Roy, L; Guimond, E

    1995-01-01

    "Demographic perspectives form an integral part in the development of electric load forecasts. These forecasts in turn are used to justify the addition and repair of generating facilities that will supply power in the coming decades. The goal of this article is to present how demographic perspectives are incorporated into the electric load forecasting in Quebec. The first part presents the methods, hypotheses and results of population and household projections used by Hydro-Quebec in updating its latest development plan. The second section demonstrates applications of such demographic projections for forecasting the electric load, with a focus on the residential sector." (SUMMARY IN ENG AND SPA) excerpt

  10. The effect of electric field maximum on the Rabi flopping and generated higher frequency spectra

    International Nuclear Information System (INIS)

    Niu Yueping; Cui Ni; Xiang Yang; Li Ruxin; Gong Shangqing; Xu Zhizhan

    2008-01-01

    We investigate the effect of the electric field maximum on the Rabi flopping and the generated higher frequency spectra properties by solving Maxwell-Bloch equations without invoking any standard approximations. It is found that the maximum of the electric field will lead to carrier-wave Rabi flopping (CWRF) through reversion dynamics which will be more evident when the applied field enters the sub-one-cycle regime. Therefore, under the interaction of sub-one-cycle pulses, the Rabi flopping follows the transient electric field tightly through the oscillation and reversion dynamics, which is in contrast to the conventional envelope Rabi flopping. Complete or incomplete population inversion can be realized through the control of the carrier-envelope phase (CEP). Furthermore, the generated higher frequency spectra will be changed from distinct to continuous or irregular with the variation of the CEP. Our results demonstrate that due to the evident maximum behavior of the electric field, pulses with different CEP give rise to different CWRFs, and then different degree of interferences lead to different higher frequency spectral features.

  11. A pseudo-panel data model of household electricity demand

    Energy Technology Data Exchange (ETDEWEB)

    Bernard, Jean-Thomas; Bolduc, Denis [GREEN, Department of Economics, Universite Laval, Quebec (Canada); Yameogo, Nadege-Desiree [Analysis Group Inc., 1080 Beaver Hill, Suite 1810, Montreal, Quebec (Canada)

    2011-01-15

    We study the dynamic behaviour of household electricity consumption on the basis of four large independent surveys conducted in the province of Quebec from 1989 to 2002. The latter region displays some rather unique features such as the very extensive use of electricity for space heating in a cold climate and the wide range of energy sources used to meet space heating requirements. We adopt approach to create 25 cohorts of households that form a pseudo-panel. The cohorts have on average 131 households. The model error terms allow for group heteroskedasticity and serial correlation. Short-run and long-run own and cross-price elasticities are statistically significant. Electricity and natural gas are estimated to be substitutes while electricity and fuel oil are complements, as it may occur in the Quebec context. The estimate of the income elasticity is not significant. Comparisons with related studies are provided. (author)

  12. Short- and long-run elasticities of electricity demand in the Korean service sector

    International Nuclear Information System (INIS)

    Lim, Kyoung-Min; Lim, Seul-Ye; Yoo, Seung-Hoon

    2014-01-01

    This paper attempts to examine the electricity demand function in the Korean service sector using the annual data covering the period 1970–2011. The short- and long-run elasticities of electricity demand with respect to price and income are empirically estimated using a co-integration and error-correction model. The short- and long-run price elasticities are estimated to be −0.421 and −1.002, respectively. The short- and long-run income elasticities are computed to be 0.855 and 1.090, respectively. Electricity demand in the service sector is inelastic to changes in both price and income in the short-run, but elastic in the long-run. Therefore, it appears that a pricing policy is more effective than the direct regulation of reducing electricity demand in the long-run in order to stabilize the electricity demand in the service sector. Moreover, it is necessary to encourage a more efficient use of electricity to cope with increasing demand for electricity following economic growth because the electricity demand in the service sector is income-elastic in the long-run. - Highlights: • We examine the electricity demand function in the Korean service sector. • We use the annual data covering the period 1970–2011. • The demand function is estimated using a co-integration and error-correction model. • The short- and long-run price elasticities are −0.421 and −1.002, respectively. • The short- and long-run income elasticities are 0.855 and 1.090, respectively

  13. Mining residential water and electricity demand data in Southern California to inform demand management strategies

    Science.gov (United States)

    Cominola, A.; Spang, E. S.; Giuliani, M.; Castelletti, A.; Loge, F. J.; Lund, J. R.

    2016-12-01

    Demand side management strategies are key to meet future water and energy demands in urban contexts, promote water and energy efficiency in the residential sector, provide customized services and communications to consumers, and reduce utilities' costs. Smart metering technologies allow gathering high temporal and spatial resolution water and energy consumption data and support the development of data-driven models of consumers' behavior. Modelling and predicting resource consumption behavior is essential to inform demand management. Yet, analyzing big, smart metered, databases requires proper data mining and modelling techniques, in order to extract useful information supporting decision makers to spot end uses towards which water and energy efficiency or conservation efforts should be prioritized. In this study, we consider the following research questions: (i) how is it possible to extract representative consumers' personalities out of big smart metered water and energy data? (ii) are residential water and energy consumption profiles interconnected? (iii) Can we design customized water and energy demand management strategies based on the knowledge of water- energy demand profiles and other user-specific psychographic information? To address the above research questions, we contribute a data-driven approach to identify and model routines in water and energy consumers' behavior. We propose a novel customer segmentation procedure based on data-mining techniques. Our procedure consists of three steps: (i) extraction of typical water-energy consumption profiles for each household, (ii) profiles clustering based on their similarity, and (iii) evaluation of the influence of candidate explanatory variables on the identified clusters. The approach is tested onto a dataset of smart metered water and energy consumption data from over 1000 households in South California. Our methodology allows identifying heterogeneous groups of consumers from the studied sample, as well as

  14. Electricity demand and conservation potential in the Chinese nonmetallic mineral products industry

    International Nuclear Information System (INIS)

    Lin, Boqiang; Ouyang, Xiaoling

    2014-01-01

    As the high energy-consuming manufacturing industry, electricity consumption of nonmetallic mineral products in China accounted for 7.93% of industrial, 5.84% of national and 1.33% of global electricity consumption in 2010. This study attempts to specify the determinants of sectoral electricity demand, forecast future electricity consumption by creating a model using the Johansen cointegration methodology and estimate the sectoral electricity conservation potential. Results indicate that GDP per capita is the leading force explaining the sectoral electricity consumption increase, while value-added per worker, R and D intensity and electricity price are the main factors contributing to the sectoral electricity consumption decrease. Results demonstrate that sectoral electricity consumption in 2020 will be 369.79–464.83 billion kWh under the low-growth scenario and 530.14–666.39 billion kWh under the high-growth scenario. Moreover, under the low-growth scenario, the sectoral electricity conservation potential in 2020 will be 33.72–95.03 billion kWh, accounting for 0.45–1.26% of China's total electricity demand in 2020; under the high-growth scenario, the sectoral electricity conservation potential in 2020 will be 48.34–136.24 billion kWh, accounting for 0.26–0.74% of world's total electricity consumption in 2010 respectively. Finally, we provide some policy recommendations for encouraging energy conservation in China's nonmetallic mineral products industry. - Highlights: • A long-term relationship of electricity demand in nonmetallic minerals industry is established. • Determinants of the sectoral electricity consumption are specified. • The sectoral electricity demand and saving potential are analyzed using scenarios analysis. • Electricity saving potential will be 48.34–136.24 billion kWh under the high-growth scenario

  15. Electricity consumption in G7 countries: A panel cointegration analysis of residential demand elasticities

    International Nuclear Information System (INIS)

    Narayan, Paresh Kumar; Smyth, Russell; Prasad, Arti

    2007-01-01

    This article applies recently developed panel unit root and panel cointegration techniques to estimate the long-run and short-run income and price elasticities for residential demand for electricity in G7 countries. The panel results indicate that in the long-run residential demand for electricity is price elastic and income inelastic. The study concludes that from an environmental perspective there is potential to use pricing policies in the G7 countries to curtail residential electricity demand, and thus curb carbon emissions, in the long run. (author)

  16. Demand participation in the restructured Electric Reliability Council of Texas market

    International Nuclear Information System (INIS)

    Zarnikau, Jay W.

    2010-01-01

    Does an electricity market which has been restructured to foster competition provide greater opportunities for demand response than a traditional regulated utility industry? The experiences of the restructured Electric Reliability Council of Texas (ERCOT) market over the past eight years provide some hope that it is possible to design a competitive market which will properly value and accommodate demand response. While the overall level of demand response in ERCOT is below the levels enjoyed prior to restructuring, there have nonetheless been some promising advances, including the integration of demand-side resources into competitive markets for ancillary services. ERCOT's experiences demonstrate that the degree of demand participation in a restructured market is highly sensitive to the market design. But even in a market which has been deregulated to a large degree, regulatory intervention and special demand-side programs may be needed in order to bolster demand response. (author)

  17. Latin American electric power developments and hydrocarbon demands

    International Nuclear Information System (INIS)

    Sanchez Sierra, G.

    1995-01-01

    Latin American countries must address issues such as financing, management (business, technical, environmental) and low-income sectors to promote the structural changes required in energy supply and demand to optimise efficient use. Private sector participation is not only a matter of ownership but raising the level of efficiency. The state's role will be to ensure stability, confidence and environmental safeguards. (author)

  18. Projected Demand and Potential Impacts to the National Airspace System of Autonomous, Electric, On-Demand Small Aircraft

    Science.gov (United States)

    Smith, Jeremy C.; Viken, Jeffrey K.; Guerreiro, Nelson M.; Dollyhigh, Samuel M.; Fenbert, James W.; Hartman, Christopher L.; Kwa, Teck-Seng; Moore, Mark D.

    2012-01-01

    Electric propulsion and autonomy are technology frontiers that offer tremendous potential to achieve low operating costs for small-aircraft. Such technologies enable simple and safe to operate vehicles that could dramatically improve regional transportation accessibility and speed through point-to-point operations. This analysis develops an understanding of the potential traffic volume and National Airspace System (NAS) capacity for small on-demand aircraft operations. Future demand projections use the Transportation Systems Analysis Model (TSAM), a tool suite developed by NASA and the Transportation Laboratory of Virginia Polytechnic Institute. Demand projections from TSAM contain the mode of travel, number of trips and geographic distribution of trips. For this study, the mode of travel can be commercial aircraft, automobile and on-demand aircraft. NASA's Airspace Concept Evaluation System (ACES) is used to assess NAS impact. This simulation takes a schedule that includes all flights: commercial passenger and cargo; conventional General Aviation and on-demand small aircraft, and operates them in the simulated NAS. The results of this analysis projects very large trip numbers for an on-demand air transportation system competitive with automobiles in cost per passenger mile. The significance is this type of air transportation can enhance mobility for communities that currently lack access to commercial air transportation. Another significant finding is that the large numbers of operations can have an impact on the current NAS infrastructure used by commercial airlines and cargo operators, even if on-demand traffic does not use the 28 airports in the Continental U.S. designated as large hubs by the FAA. Some smaller airports will experience greater demand than their current capacity allows and will require upgrading. In addition, in future years as demand grows and vehicle performance improves other non-conventional facilities such as short runways incorporated into

  19. Simulating demand for electric vehicles using revealed preference data

    International Nuclear Information System (INIS)

    Driscoll, Áine; Lyons, Seán; Mariuzzo, Franco; Tol, Richard S.J.

    2013-01-01

    We have modelled the market for new cars in Ireland with the aim of quantifying the values placed on a range of observable car characteristics. Mid-sized petrol cars with a manual transmission sell best. Price and perhaps fuel cost are negatively associated with sales, and acceleration and perhaps range are positively associated. Hybrid cars are popular. The values of car characteristics are then used to simulate the likely market shares of three new electric vehicles. Electric vehicles tend to be more expensive even after tax breaks and subsidies are applied, but we assume their market shares would benefit from an “environmental” premium similar to those of hybrid cars. The “environmental” premium and the level of subsidies would need to be raised to incredible levels to reach the government target of 10% market penetration of all-electric vehicles. -- Highlights: •Market values placed on a range of observable car characteristics are quantified. •We simulate market shares of electrical vehicles from values of car characteristics. •We assume electric vehicles will benefit from an “environmental” premium. •Large premium not enough to reach government targets for market penetration. •Very high subsidies required to reach government targets for market penetration

  20. Analysis of the electricity supply-demand balance for the winter period 2009-2010

    International Nuclear Information System (INIS)

    2009-10-01

    Every year, RTE conducts a prospective study of the balance between supply and demand for electricity for the coming winter period, covering the whole of mainland France. This period of the year is looked at closely, primarily due to the high levels of electricity demand seen during cold snaps. The study by RTE is used to identify periods where the supply-demand balance comes under strain; it explores the measures that can be taken by electricity market players and RTE to avoid any interruption in supply during peak demand periods in France. RTE is responsible for managing the balance between supply and demand for electricity in mainland France, in real time. To do this, it anticipates potential risks that may supply may come under strain - well in advance - and informs market players. If periods are identified where the supply-demand balance comes under strain, RTE works with the electricity generators to look at possible ways of altering the schedules for shutting down generating units, and takes account of the possibilities for demand response (load reduction) reported by suppliers. As a last resort, if these preemptive measures prove insufficient and the situation becomes critical, RTE alerts the government of the risk that supply will be interrupted, and takes action in real time to limit the impact on the power system. For temperatures close to seasonal norms, the forecast outlook for the electricity supply-demand balance appears significantly less favourable than last winter until the end of January. Imports could be required between mid-November 2009 and the end of January 2010, to cover electricity demand in France and satisfy the technical security margin stipulated by RTE. To do this, suppliers would have to look to the European markets, in addition to activating demand response (load reduction) possibilities with their customer portfolios. In the event of an intense and sustained spell of cold weather, the technical limit for imports into the French

  1. Electric power supply and demand for the contiguous United States, 1980-1989

    Energy Technology Data Exchange (ETDEWEB)

    None

    1980-06-01

    A limited review is presented of the outlook for the electric power supply and demand during the period 1980 to 1989. Only the adequacy and reliability aspects of bulk electric power supply in the contiguous US are considered. The economic, financial and environmental aspects of electric power system planning and the distribution of electricity (below the transmission level) are topics of prime importance, but they are outside the scope of this report.

  2. Time-of-use based electricity demand response for sustainable manufacturing systems

    International Nuclear Information System (INIS)

    Wang, Yong; Li, Lin

    2013-01-01

    As required by the Energy Policy Act of 2005, utility companies across the U.S. are offering TOU (time-of-use) based electricity demand response programs. The TOU rate gives consumers opportunities to manage their electricity bill by shifting use from on-peak periods to mid-peak and off-peak periods. Reducing the amount of electricity needed during the peak load times makes it possible for the power grid to meet consumers' needs without building more costly backup infrastructures and help reduce GHG (greenhouse gas) emissions. Previous research on the applications of TOU and other electricity demand response programs has been mainly focused on residential and commercial buildings while largely neglected industrial manufacturing systems. This paper proposes a systems approach for TOU based electricity demand response for sustainable manufacturing systems under the production target constraint. Key features of this approach include: (i) the electricity related costs including both consumption and demand are integrated into production system modeling; (ii) energy-efficient and demand-responsive production scheduling problems are formulated and the solution technique is provided; and (iii) the effects of various factors on the near-optimal scheduling solutions are examined. The research outcome is expected to enhance the energy efficiency, electricity demand responsiveness, and cost effectiveness of modern manufacturing systems. - Highlights: • We propose a TOU based demand response approach for manufacturing systems. • Both electricity consumption and demand are integrated into the system modeling. • Energy-efficient and demand-responsive production scheduling problems are formulated. • The meta-heuristic solution technique is provided. • The effects of various factors on the scheduling solutions are examined

  3. The Power of Electric Vehicles - Exploring the Value of Flexible Electricity Demand in a Multi-actor Context

    NARCIS (Netherlands)

    Verzijlbergh, R.A.

    2013-01-01

    Electric vehicles (EVs) have the potential to play a crucial role in clean and intelligent power systems. The key to this potential lies in the flexibility that EVs provide by the ability to shift their electricity demand in time. This flexibility can be used to facilitate the integration of

  4. Short- and long-run time-of-use price elasticities in Swiss residential electricity demand

    International Nuclear Information System (INIS)

    Filippini, Massimo

    2011-01-01

    This paper presents an empirical analysis on the residential demand for electricity by time-of-day. This analysis has been performed using aggregate data at the city level for 22 Swiss cities for the period 2000-2006. For this purpose, we estimated two log-log demand equations for peak and off-peak electricity consumption using static and dynamic partial adjustment approaches. These demand functions were estimated using several econometric approaches for panel data, for example LSDV and RE for static models, and LSDV and corrected LSDV estimators for dynamic models. The attempt of this empirical analysis has been to highlight some of the characteristics of the Swiss residential electricity demand. The estimated short-run own price elasticities are lower than 1, whereas in the long-run these values are higher than 1. The estimated short-run and long-run cross-price elasticities are positive. This result shows that peak and off-peak electricity are substitutes. In this context, time differentiated prices should provide an economic incentive to customers so that they can modify consumption patterns by reducing peak demand and shifting electricity consumption from peak to off-peak periods. - Highlights: → Empirical analysis on the residential demand for electricity by time-of-day. → Estimators for dynamic panel data. → Peak and off-peak residential electricity are substitutes.

  5. Demand for power in Calcutta Electricity Supply Corporation area

    Energy Technology Data Exchange (ETDEWEB)

    Banerjee, N

    1980-07-01

    Since the early 1970's there has been a continuous crisis of power supply to the Calcutta industrial region. Historical records show that only the peak demand has grown and has a potential for growth, which, with an unchanging base demand, results in a low load factor and consequently inefficient power system operation. Attempts to shift industrial loads by operating industrial plants during non-peak hours are described. Adverse economic conditions eliminated the need for extra working shifts. It is concluded that the power system supplying the Calcutta region has an insufficient peak load generating capacity and an uneconomic load curve and that stricter hourly schedules for power use by industries should be adhered to in order to minimize these problems. (LCL)

  6. Operational demands as determining factor for electric bus charging infrastructure

    NARCIS (Netherlands)

    Beekman, R.; Van Den Hoed, R.

    2016-01-01

    Many cities in Europe have ambitious goals when it comes to making their public transport buses emission free. This article outlines the reasoning behind the choices made in the city of Amsterdam with regards to charging infrastructure for electric buses. Emphasising the importance of operational

  7. Interim report by a Committee on Demands and Supplies of Electric Enterprise Council

    International Nuclear Information System (INIS)

    1984-01-01

    An interim report by a committee on demands and supplies, Electric Enterprise Council, was given for the period up to the year 2000. The demands of electric power in Japan were set as 658,000 million kWh for 1990 and 768,000 million kWh for 1995. The electric power enterprises appear to be at a major turning point at present, that is, the growth in the demands tended to slow down. The features of the situation are then the stabilized supply, supply cost reduction, reasonable power source constitution, etc. The following things are described. Background and policy; power demand outlook and supply measures; power supply and supply efficiency (the composition of power sources, respective power sources with supply targets and problems, etc.); power demand/supply outlook for 2000. (Mori, K.)

  8. The electric energy demand-side planning: necessity and possibilities of execution

    International Nuclear Information System (INIS)

    Sposito, E.S.

    1991-05-01

    Aiming at reducing the level of investments, is presented a demand-side planning approach, divided into two parts. The first part is an analysis on the actual need of our demand-side approaching. In view of this, is showed a set of data and comments both on economic and technological aspects concerning the electric network and sector, as well as evaluation of the social, ecological and financial aspects which could act against the full expansion of the electric system. In the second part, a demand-side planning methodology is introduced, as well as its main concepts, its variables and its instruments of affecting the demand: energy conservation, replacement of sources, reduction of losses and electric power decentralized generation. Each of them is fully detailed in a set of planning policies and actions. Concluding is presented the basic elements of a National Electric Energy Substitution and Conservation Plan - PLANSCON. (author)

  9. A Review of Demand Forecast for Charging Facilities of Electric Vehicles

    Science.gov (United States)

    Jiming, Han; Lingyu, Kong; Yaqi, Shen; Ying, Li; Wenting, Xiong; Hao, Wang

    2017-05-01

    The demand forecasting of charging facilities is the basis of its planning and locating, which has important role in promoting the development of electric vehicles and alleviating the energy crisis. Firstly, this paper analyzes the influence of the charging mode, the electric vehicle population and the user’s charging habits on the demand of charging facilities; Secondly, considering these factors, the recent analysis on charging and switching equipment demand forecast is divided into two methods—forecast based on electric vehicle population and user traveling behavior. Then, the article analyzes the two methods and puts forward the advantages and disadvantages. Finally, in view of the defects of current research, combined with the current situation of the development of the city and comprehensive consideration of economic, political, environmental and other factors, this paper proposes an improved demand forecasting method which has great practicability and pertinence and lays the foundation for the plan of city electric facilities.

  10. Prospective Life Cycle Assessment of the Increased Electricity Demand Associated with the Penetration of Electric Vehicles in Spain

    Directory of Open Access Journals (Sweden)

    Zaira Navas-Anguita

    2018-05-01

    Full Text Available The penetration of electric vehicles (EV seems to be a forthcoming reality in the transport sector worldwide, involving significant increases in electricity demand. However, many countries such as Spain have not yet set binding policy targets in this regard. When compared to a business-as-usual situation, this work evaluates the life-cycle consequences of the increased electricity demand of the Spanish road transport technology mix until 2050. This is done by combining Life Cycle Assessment and Energy Systems Modelling under three alternative scenarios based on the low, medium, or high penetration rate of EV. In all cases, EV deployment is found to involve a relatively small percentage (<4% of the final electricity demand. Wind power and waste-to-energy plants arise as the main technologies responsible for meeting the increased electricity demand associated with EV penetration. When considering a high market penetration (20 million EV by 2050, the highest annual impacts potentially caused by the additional electricity demand are 0.93 Mt CO2 eq, 0.25 kDALY, and 30.34 PJ in terms of climate change, human health, and resources, respectively. Overall, EV penetration is concluded to slightly affect the national power generation sector, whereas it could dramatically reduce the life-cycle impacts associated with conventional transport.

  11. The Use of Artificial Neural Networks for Forecasting the Electric Demand of Stand-Alone Consumers

    Science.gov (United States)

    Ivanin, O. A.; Direktor, L. B.

    2018-05-01

    The problem of short-term forecasting of electric power demand of stand-alone consumers (small inhabited localities) situated outside centralized power supply areas is considered. The basic approaches to modeling the electric power demand depending on the forecasting time frame and the problems set, as well as the specific features of such modeling, are described. The advantages and disadvantages of the methods used for the short-term forecast of the electric demand are indicated, and difficulties involved in the solution of the problem are outlined. The basic principles of arranging artificial neural networks are set forth; it is also shown that the proposed method is preferable when the input information necessary for prediction is lacking or incomplete. The selection of the parameters that should be included into the list of the input data for modeling the electric power demand of residential areas using artificial neural networks is validated. The structure of a neural network is proposed for solving the problem of modeling the electric power demand of residential areas. The specific features of generation of the training dataset are outlined. The results of test modeling of daily electric demand curves for some settlements of Kamchatka and Yakutia based on known actual electric demand curves are provided. The reliability of the test modeling has been validated. A high value of the deviation of the modeled curve from the reference curve obtained in one of the four reference calculations is explained. The input data and the predicted power demand curves for the rural settlement of Kuokuiskii Nasleg are provided. The power demand curves were modeled for four characteristic days of the year, and they can be used in the future for designing a power supply system for the settlement. To enhance the accuracy of the method, a series of measures based on specific features of a neural network's functioning are proposed.

  12. A Study on Grid-Square Statistics Based Estimation of Regional Electricity Demand and Regional Potential Capacity of Distributed Generators

    Science.gov (United States)

    Kato, Takeyoshi; Sugimoto, Hiroyuki; Suzuoki, Yasuo

    We established a procedure for estimating regional electricity demand and regional potential capacity of distributed generators (DGs) by using a grid square statistics data set. A photovoltaic power system (PV system) for residential use and a co-generation system (CGS) for both residential and commercial use were taken into account. As an example, the result regarding Aichi prefecture was presented in this paper. The statistical data of the number of households by family-type and the number of employees by business category for about 4000 grid-square with 1km × 1km area was used to estimate the floor space or the electricity demand distribution. The rooftop area available for installing PV systems was also estimated with the grid-square statistics data set. Considering the relation between a capacity of existing CGS and a scale-index of building where CGS is installed, the potential capacity of CGS was estimated for three business categories, i.e. hotel, hospital, store. In some regions, the potential capacity of PV systems was estimated to be about 10,000kW/km2, which corresponds to the density of the existing area with intensive installation of PV systems. Finally, we discussed the ratio of regional potential capacity of DGs to regional maximum electricity demand for deducing the appropriate capacity of DGs in the model of future electricity distribution system.

  13. Energy-environment policy goals and instruments and electricity demand response. A framework for the analysis

    International Nuclear Information System (INIS)

    Rio, Pablo del; Hernandez, F.

    2004-01-01

    The environment and energy realms have traditionally been two major focus of attention of EU and Member State (MS) policy. This attention has intensified in recent years as a response to, both, internal and external events and strategies (i.e., the Kyoto Protocol). In this context, the EU and its MS have set ambitious goals in the environmental and energy contexts and are already implementing packages of policies and measures. Both policies interact. Although there might be conflicts between both, there are also mutually reinforcing effects with significant policy implications. Actually, as stated in the Amsterdam Treaty, environmental protection is one of the major goals of energy policy (together with 'security of supply' and 'competitive energy systems'). On the other hand, the energy sector is instrumental in the success of environmental policy. In this context, a wide array of measures are currently being implemented in the EU and its MS which have a more or less direct impact on the electricity market. Particularly, Demand Side Management (DSM) activities, promotion of electricity from renewable energy sources (RES-E) and measures aimed at the mitigation of Greenhouse Gas (GHG) emissions are arguably three major instruments which have the potential to contribute to energy and environmental goals. The effectiveness and impact of there measures depends to a large extent on the demand response in the electricity market. Some of there measures affect the electricity demand curve, while others do not have a direct impact on the demand curve but affect the quantity of electricity demand by displacing the electricity supply curve. In turn, the effectiveness of energy and environmental policies may be different when electricity demand response varies (i.e., different elasticity demand). This paper entails an initial effort to provide a theoretical framework for the analysis of the interactions between electricity demand response and the above mentioned energy

  14. Electric shovels meet the demands for mining operations

    Energy Technology Data Exchange (ETDEWEB)

    Fiscor, S.

    2008-03-15

    Rugged, intelligent shovels offer better productivity and help mine operators avoid costly downtime in a very tight market. In 2007 P & H Mining Equipment began to produce a new breed of electric mining shovels designed to help reduce operating cost in coal and other mining operations. These were designated the P & H C-Series. All have an advanced communication, command and control system called the Centurion system. Coal mining applications for this series include 4100XPCs in Australia, China and Wyoming, USA. The Centurion system provides information on shovel performance and systems health which is communicated via graphic user interface terminals to the operators cab. Bucyrus International is developing a hydraulic crowd mechanism for its electric shovels and is now field testing one for its 495 series shovel. The company has also added greater capability in the primary software in the drive system for troubleshooting and fault identification to quickly diagnose problems onboard or remotely. 4 photos.

  15. The evolution of price elasticity of electricity demand in South Africa: A Kalman filter application

    International Nuclear Information System (INIS)

    Inglesi-Lotz, R.

    2011-01-01

    In South Africa, the electricity mismatch of supply and demand has been of major concern. Additional to past problems, the 2008 electricity crisis made the solution crucial after its damaging consequences to the economy. The disagreement on the need and consequences of the continuous electricity price hikes worsens the situation. To contribute to the recent electricity debate, this paper proposes a time-varying price elasticity of demand for electricity; the sensitivity of electricity consumption to price fluctuations changes throughout the years. The main purpose of this study is the estimation of the price elasticity of electricity in South Africa during the period 1980-2005 by employing an advanced econometric technique, the Kalman filter. Apart from the decreasing effect of electricity prices to consumption (-71.8% in the 1990s and -94.5% in the 2000s in average), our results conclude to an important finding: the higher the prices (for example in the 1980s) the higher the sensitivity of consumers to price fluctuations. Thus, further increases of the electricity prices may lead to changes in the behaviour of electricity consumers, focusing their efforts on improving their efficiency levels by introducing demand-side management techniques or even turning to other sources of - cheaper - energy. - Highlights: → The price elasticity of South Africa's electricity demand (1980-2005) is examined. → The Kalman filter methodology is used to show elasticity changes over time. → Decreasing effect of electricity prices to consumption over the years is found. → The higher the prices of electricity were, the higher the sensitivity of consumption. → If electricity prices increase, consumers will choose to consume more efficiently.

  16. The evolution of price elasticity of electricity demand in South Africa: A Kalman filter application

    Energy Technology Data Exchange (ETDEWEB)

    Inglesi-Lotz, R., E-mail: roula.inglesi@up.ac.za [Department of Economics, EMS Building, University of Pretoria, Gauteng 0002 (South Africa)

    2011-06-15

    In South Africa, the electricity mismatch of supply and demand has been of major concern. Additional to past problems, the 2008 electricity crisis made the solution crucial after its damaging consequences to the economy. The disagreement on the need and consequences of the continuous electricity price hikes worsens the situation. To contribute to the recent electricity debate, this paper proposes a time-varying price elasticity of demand for electricity; the sensitivity of electricity consumption to price fluctuations changes throughout the years. The main purpose of this study is the estimation of the price elasticity of electricity in South Africa during the period 1980-2005 by employing an advanced econometric technique, the Kalman filter. Apart from the decreasing effect of electricity prices to consumption (-71.8% in the 1990s and -94.5% in the 2000s in average), our results conclude to an important finding: the higher the prices (for example in the 1980s) the higher the sensitivity of consumers to price fluctuations. Thus, further increases of the electricity prices may lead to changes in the behaviour of electricity consumers, focusing their efforts on improving their efficiency levels by introducing demand-side management techniques or even turning to other sources of - cheaper - energy. - Highlights: > The price elasticity of South Africa's electricity demand (1980-2005) is examined. > The Kalman filter methodology is used to show elasticity changes over time. > Decreasing effect of electricity prices to consumption over the years is found. > The higher the prices of electricity were, the higher the sensitivity of consumption. > If electricity prices increase, consumers will choose to consume more efficiently.

  17. The value of online information for demand response in Walrasian electricity markets

    NARCIS (Netherlands)

    F.N. Claessen (Felix); B.J. Liefers (Bart); M. Kaisers (Michael); J.A. La Poutré (Han)

    2015-01-01

    textabstractSmart energy systems integrate renewables and demand response. Most European electricity markets coordinate the resulting time-varying flexibility in demand and supply by organising day-ahead trade with Walrasian mechanisms, using simultaneous call auctions and sealed bids. These

  18. Electricity supply and demand scenarios for the Southern African power pool

    CSIR Research Space (South Africa)

    Spalding-Fecher, R

    2017-02-01

    Full Text Available The study presents long-term electricity supply and demand scenarios for the twelve countries in the Southern African Power Pool, based on detailed bottom-up demand analysis for all countries and a set of internally consistent development scenarios...

  19. Demand-side management pricing options in electric utilities

    International Nuclear Information System (INIS)

    Sardana, P.; Herman, P.

    1990-01-01

    In 1989 Ontario Hydro implemented optional time-of-use (TOU) rates at the wholesale level for all municipal utilities in the province. At the same time, mandatory TOU rates were implemented for large users (customers with loads in excess of 5 MW) served by municipal utilities and Ontario Hydro's direct customers. To fully explore the potential of rate structures as demand-side management (DSM) tools, Ontario Hydro retained a consulting firm to carry out a survey of innovative rate structures in other jurisdications. The survey was intended to identify: the status quo of rate structures in other jurisdictions that were designed specifically to encourage DSM; a profile of the cost basis of the rate structures, for example whether traditional embedded cost of service analyses or contentious methods such as marginal cost pricing were used; whether innovative rates have been successful, and customer reactions and attitudes; and how innovative rates fit into the overall strategy of the utilities. It was found that TOU, interruptible and end-use targeted rates are the rate structures of choice for many utilities. Most are concerned with deferring capacity, reducing peak demand, and shifting load out of peak periods. Most utilities report success with their programs and satisfaction with the present form of the programs. 5 tabs

  20. Estimating short and long-term residential demand for electricity. New evidence from Sri Lanka

    International Nuclear Information System (INIS)

    Athukorala, P.P.A Wasantha; Wilson, Clevo

    2010-01-01

    This study investigates the short-run dynamics and long-run equilibrium relationship between residential electricity demand and factors influencing demand - per capita income, price of electricity, price of kerosene oil and price of liquefied petroleum gas - using annual data for Sri Lanka for the period, 1960-2007. The study uses unit root, cointegration and error-correction models. The long-run demand elasticities of income, own price and price of kerosene oil (substitute) were estimated to be 0.78, - 0.62, and 0.14 respectively. The short-run elasticities for the same variables were estimated to be 0.32, - 0.16 and 0.10 respectively. Liquefied petroleum (LP) gas is a substitute for electricity only in the short-run with an elasticity of 0.09. The main findings of the paper support the following (1) increasing the price of electricity is not the most effective tool to reduce electricity consumption (2) existing subsidies on electricity consumption can be removed without reducing government revenue (3) the long-run income elasticity of demand shows that any future increase in household incomes is likely to significantly increase the demand for electricity and (4) any power generation plans which consider only current per capita consumption and population growth should be revised taking into account the potential future income increases in order to avoid power shortages in the country. (author)

  1. Turkey's short-term gross annual electricity demand forecast by fuzzy logic approach

    International Nuclear Information System (INIS)

    Kucukali, Serhat; Baris, Kemal

    2010-01-01

    This paper aims to forecast Turkey's short-term gross annual electricity demand by applying fuzzy logic methodology while general information on economical, political and electricity market conditions of the country is also given. Unlike most of the other forecast models about Turkey's electricity demand, which usually uses more than one parameter, gross domestic product (GDP) based on purchasing power parity was the only parameter used in the model. Proposed model made good predictions and captured the system dynamic behavior covering the years of 1970-2014. The model yielded average absolute relative errors of 3.9%. Furthermore, the model estimates a 4.5% decrease in electricity demand of Turkey in 2009 and the electricity demand growth rates are projected to be about 4% between 2010 and 2014. It is concluded that forecasting the Turkey's short-term gross electricity demand with the country's economic performance will provide more reliable projections. Forecasting the annual electricity consumption of a country could be made by any designer with the help of the fuzzy logic procedure described in this paper. The advantage of this model lies on the ability to mimic the human thinking and reasoning.

  2. Estimating short and long-term residential demand for electricity. New evidence from Sri Lanka

    Energy Technology Data Exchange (ETDEWEB)

    Athukorala, P.P.A Wasantha; Wilson, Clevo [School of Economics and Finance, Queensland University of Technology, Brisbane (Australia)

    2010-09-15

    This study investigates the short-run dynamics and long-run equilibrium relationship between residential electricity demand and factors influencing demand - per capita income, price of electricity, price of kerosene oil and price of liquefied petroleum gas - using annual data for Sri Lanka for the period, 1960-2007. The study uses unit root, cointegration and error-correction models. The long-run demand elasticities of income, own price and price of kerosene oil (substitute) were estimated to be 0.78, - 0.62, and 0.14 respectively. The short-run elasticities for the same variables were estimated to be 0.32, - 0.16 and 0.10 respectively. Liquefied petroleum (LP) gas is a substitute for electricity only in the short-run with an elasticity of 0.09. The main findings of the paper support the following (1) increasing the price of electricity is not the most effective tool to reduce electricity consumption (2) existing subsidies on electricity consumption can be removed without reducing government revenue (3) the long-run income elasticity of demand shows that any future increase in household incomes is likely to significantly increase the demand for electricity and (4) any power generation plans which consider only current per capita consumption and population growth should be revised taking into account the potential future income increases in order to avoid power shortages in the country. (author)

  3. Turkey's short-term gross annual electricity demand forecast by fuzzy logic approach

    Energy Technology Data Exchange (ETDEWEB)

    Kucukali, Serhat [Civil Engineering Department, Zonguldak Karaelmas University, Incivez 67100, Zonguldak (Turkey); Baris, Kemal [Mining Engineering Department, Zonguldak Karaelmas University, Incivez 67100, Zonguldak (Turkey)

    2010-05-15

    This paper aims to forecast Turkey's short-term gross annual electricity demand by applying fuzzy logic methodology while general information on economical, political and electricity market conditions of the country is also given. Unlike most of the other forecast models about Turkey's electricity demand, which usually uses more than one parameter, gross domestic product (GDP) based on purchasing power parity was the only parameter used in the model. Proposed model made good predictions and captured the system dynamic behavior covering the years of 1970-2014. The model yielded average absolute relative errors of 3.9%. Furthermore, the model estimates a 4.5% decrease in electricity demand of Turkey in 2009 and the electricity demand growth rates are projected to be about 4% between 2010 and 2014. It is concluded that forecasting the Turkey's short-term gross electricity demand with the country's economic performance will provide more reliable projections. Forecasting the annual electricity consumption of a country could be made by any designer with the help of the fuzzy logic procedure described in this paper. The advantage of this model lies on the ability to mimic the human thinking and reasoning. (author)

  4. Power converter with maximum power point tracking MPPT for small wind-electric pumping systems

    International Nuclear Information System (INIS)

    Lara, David; Merino, Gabriel; Salazar, Lautaro

    2015-01-01

    Highlights: • We implement a wind electric pumping system of small power. • The power converter allowed to change the operating point of the electro pump. • Two control techniques were implemented in the power converter. • The control V/f variable allowed to increase the power generated by the permanent magnet generator. - Abstract: In this work, an AC–DC–AC direct-drive power converter was implemented for a wind electric pumping system consisting of a permanent magnet generator (PMG) of 1.3 kW and a peripheral single phase pump of 0.74 kW. In addition, the inverter linear V/f control scheme and the maximum power point tracking (MPPT) algorithm with variable V/f were developed. MPPT algorithm seeks to extract water in a wide range of power input using the maximum amount of wind power available. Experimental trials at different pump pressures were conducted. With a MPPT tracking system with variable V/f, a power value of 1.3 kW was obtained at a speed of 350 rpm and a maximum operating hydraulic head of 50 m. At lower operating heads pressures (between 10 and 40 m), variable V/f control increases the power generated by the PMG compared to the linear V/f control. This increase ranged between 4% and 23% depending on the operating pressure, with an average of 13%, getting close to the maximum electrical power curve of the PMG. The pump was driven at variable frequency reaching a minimum speed of 0.5 times the rated speed. Efficiency of the power converter ranges between 70% and 95% with a power factor between 0.4 and 0.85, depending on the operating pressure

  5. Assessment of end-use electricity consumption and peak demand by Townsville's housing stock

    International Nuclear Information System (INIS)

    Ren, Zhengen; Paevere, Phillip; Grozev, George; Egan, Stephen; Anticev, Julia

    2013-01-01

    We have developed a comprehensive model to estimate annual end-use electricity consumption and peak demand of housing stock, considering occupants' use of air conditioning systems and major appliances. The model was applied to analyse private dwellings in Townsville, Australia's largest tropical city. For the financial year (FY) 2010–11 the predicted results agreed with the actual electricity consumption with an error less than 10% for cooling thermostat settings at the standard setting temperature of 26.5 °C and at 1.0 °C higher than the standard setting. The greatest difference in monthly electricity consumption in the summer season between the model and the actual data decreased from 21% to 2% when the thermostat setting was changed from 26.5 °C to 27.5 °C. Our findings also showed that installation of solar panels in Townville houses could reduce electricity demand from the grid and would have a minor impact on the yearly peak demand. A key new feature of the model is that it can be used to predict probability distribution of energy demand considering (a) that appliances may be used randomly and (b) the way people use thermostats. The peak demand for the FY estimated from the probability distribution tracked the actual peak demand at 97% confidence level. - Highlights: • We developed a model to estimate housing stock energy consumption and peak demand. • Appliances used randomly and thermostat settings for space cooling were considered. • On-site installation of solar panels was also considered. • Its' results agree well with the actual electricity consumption and peak demand. • It shows the model could provide the probability distribution of electricity demand

  6. A speculation on the debate about the future electricity demand in Korea

    International Nuclear Information System (INIS)

    Lim, Chae Young; Moon, Kee Hwan

    2005-01-01

    Since 1991, Korean government established the Long term Power Development Plan(LPDP) to secure a stable electricity supply. With the introduction of market mechanism into electricity supply sector, that plan has been changed into the Basic Plan of the Electricity supply and demand(BPE), which plays a role as a nonbinding guideline or a reference rather than the implementation plan. The BPE still has its importance as a tool providing market participants with appropriate information of future electricity market. According to the second BPE, released at the end of 2004, electricity demand is projected to grow at 2.5% per annum and reach 416.5TWh in 2017 from 293.6TWh in 2003. Based on the projected demand, power expansion plan provided by utilities has established. In the process of formulating the BPE, there were hot debates on the excess capacity margins for certain period of planning time. Some people, especially from environmental groups maintained that many Koreans were wasteful with electricity so that stronger policy for curbing the electricity consumption should be introduced rather than commissioning of additional power plants. They referred to relatively high number of the electricity intensity of Korea as the grounds of their argument. However, electricity intensity in a region or a country is influenced by various factors and higher intensity does not necessarily mean more wasteful consumption of electricity. We have compared various aspects of electricity demand in Korea with other countries to speculate the argument that electricity consumption in Korea is too high. We have also discussed electricity projection in the BPE

  7. Maximum power point tracking analysis of a coreless ironless electric generator for renewable energy application

    Science.gov (United States)

    Razali, Akhtar; Rahman, Fadhlur; Leong, Yap Wee; Razali Hanipah, Mohd; Azri Hizami, Mohd

    2018-04-01

    The magnetism attraction between permanent magnets and soft ironcore lamination in a conventional electric ironcore generator is often known as cogging. Cogging requires an additional input power to overcome, hence became one of the power loss sources. With the increasing of power output, the cogging is also proportionally increased. This leads to the increasing of the supplied power of the driver motor to overcome the cog. Therefore, this research is embarked to study fundamentally about the possibility of removing ironcore lamination in an electric generator to see its performance characteristic. In the maximum power point tracking test, the fabricated ironless coreless electricity generator was tested by applying the load on the ironless coreless electricity generator optimization to maximize the power generated, voltage and the current produced by the ironless coreless electricity generator when the rotational speed of the rotor increased throughout the test. The rotational torque and power output are measured, and efficiency is then analyzed. Results indicated that the generator produced RMS voltage of 200VAC at rotational speed of 318 RPM. Torque required to rotate the generator was at 10.8Nm. The generator had working efficiency of 77.73% and the power generated was at 280W.

  8. Saving, efficiency and management of electric sector demand

    International Nuclear Information System (INIS)

    Sanchez de Tembleque, L. J.

    2007-01-01

    Spanish economic model of development is based on energy consumption, and its main source is imported fossil fuels, which have some environmental and scarcity consequences in the mid term, among others. These problems could be reduced in two ways: economic activity reduction or energy efficiency improvement. In the presence of these possibilities, It may be desirable to bet for saving and energy efficiency, to maintain the economic development. This assignment analyzes the main available regulatory and social mechanisms to promote saving and energy efficiency in the power sector, like systems to internalize social costs in the electricity price, efficiency standards, and encourage the new saving culture. (Author) 15 refs

  9. Study of some aspects of the long-run domestic demand for electricity in New Zealand

    Energy Technology Data Exchange (ETDEWEB)

    Stent, A F

    1982-01-01

    This study investigates the long-run domestic demand for electricity in New Zealand over the period 1945 to 1972. The first part analyzes the ownership of electrical appliances using data from the five yearly censuses of population and dwellings. A dynamic appliance ownership model is developed for the analysis. This model explains the proportion of households, in small regional districts, with ownership status of a particular appliance type when observed at census time. It measures the effects of prices, income, and household taste characteristics on ownership. The main results include estimates of long-run electricity price effects. The second part of the thesis estimates dynamic demand equations for electricity. A flow-adjustment model is fitted to moving cross sections of data for individual Electrical Supply Authority districts in the North and South Islands separately. The final part of the thesis undertakes a synthesis of electricity price effects on appliance ownership (from the first part) and electricity demand (from the second part). This indicates substantial consistency in the estimates obtained. The main conclusions for electricity price are that this variable has been a significant factor in explaining the variation in domestic electricity consumption over the period; that the relationship has been inelastic in the later part, in both short and long-runs; and that long-run effects are mainly via the use of the electrical services.

  10. Energy management for vehicle power net with flexible electric load demand

    NARCIS (Netherlands)

    Kessels, J.T.B.A.; Bosch, van den P.P.J.; Koot, M.W.T.; Jager, de A.G.

    2005-01-01

    The electric power demand in road vehicles increases rapidly and to supply all electric loads efficiently, energy management (EM) turns out to be a necessity. In general, EM exploits the storage capacity of a buffer connected to the vehicle's power net, such that energy is stored or retrieved at

  11. Optimal Electricity Charge Strategy Based on Price Elasticity of Demand for Users

    Science.gov (United States)

    Li, Xin; Xu, Daidai; Zang, Chuanzhi

    The price elasticity is very important for the prediction of electricity demand. This paper mainly establishes the price elasticity coefficient for electricity in single period and inter-temporal. Then, a charging strategy is established based on these coefficients. To evaluate the strategy proposed, simulations of the two elastic coefficients are carried out based on the history data of a certain region.

  12. The demand for electricity in Australia to 2020

    International Nuclear Information System (INIS)

    Orchison, K.

    2003-01-01

    Pursuing a secure, reliable electricity supply, therefore, is easily explained as a high national priority here as elsewhere and the cost of doing so in the next 12-20 years will be measured in billions of dollars - according to ESAA calculations, some $30 billion by 2012 and probably more than $40 billion by 2020, not including the billions likely to be needed to ensure an adequate supply of natural gas to generators. In any scenario that makes sense to ESAA, natural gas, black coal and brown coal will dominate as fuels for electricity generation. Obviously, renewable energy, driven by government subsidy through a program that mandates retailer purchases, will grow in use, but at 2020 it is not remotely likely that fossil fuels will have less than 80 percent of the generation mix. A brief word here about the prospect for nuclear power use in Australia in this time frame. ESAA simply cannot see a nuclear development being pursued - for political reasons if for no other

  13. A long- and short-run analysis of electricity demand in Ciudad Juarez

    Science.gov (United States)

    Mendez-Carrillo, Ericka Cecilia

    Economic growth and appliance saturation are increasing electricity consumption in Mexico. Annual frequency data from 1990 to 2012 are utilized to develop an error correction framework that sheds light on short- and long-run electricity consumption behavior in Ciudad Juarez, a large Mexican metropolitan economy at the border with the United States. The results for this study reveal that electricity is an inelastic normal good in this market. Moreover, natural gas is found to be a weak complement to electricity. With regards to the customer base in this urban economy, population, employment, and income exercise positive and statistically significant impacts on the demand for electricity hook-ups.

  14. Energy Systems Scenario Modelling and Long Term Forecasting of Hourly Electricity Demand

    DEFF Research Database (Denmark)

    Alberg Østergaard, Poul; Møller Andersen, Frits; Kwon, Pil Seok

    2015-01-01

    . The results show that even with a limited short term electric car fleet, these will have a significant effect on the energy system; the energy system’s ability to integrate wind power and the demand for condensing power generation capacity in the system. Charging patterns and flexibility have significant...... or inflexible electric vehicles and individual heat pumps, and in the long term it is investigated what the effects of changes in the load profiles due to changing weights of demand sectors are. The analyses are based on energy systems simulations using EnergyPLAN and demand forecasting using the Helena model...... effects on this. Likewise, individual heat pumps may affect the system operation if they are equipped with heat storages. The analyses also show that the long term changes in electricity demand curve profiles have little impact on the energy system performance. The flexibility given by heat pumps...

  15. The UK-DALE dataset, domestic appliance-level electricity demand and whole-house demand from five UK homes

    Science.gov (United States)

    Kelly, Jack; Knottenbelt, William

    2015-03-01

    Many countries are rolling out smart electricity meters. These measure a home’s total power demand. However, research into consumer behaviour suggests that consumers are best able to improve their energy efficiency when provided with itemised, appliance-by-appliance consumption information. Energy disaggregation is a computational technique for estimating appliance-by-appliance energy consumption from a whole-house meter signal. To conduct research on disaggregation algorithms, researchers require data describing not just the aggregate demand per building but also the ‘ground truth’ demand of individual appliances. In this context, we present UK-DALE: an open-access dataset from the UK recording Domestic Appliance-Level Electricity at a sample rate of 16 kHz for the whole-house and at 1/6 Hz for individual appliances. This is the first open access UK dataset at this temporal resolution. We recorded from five houses, one of which was recorded for 655 days, the longest duration we are aware of for any energy dataset at this sample rate. We also describe the low-cost, open-source, wireless system we built for collecting our dataset.

  16. The UK-DALE dataset, domestic appliance-level electricity demand and whole-house demand from five UK homes.

    Science.gov (United States)

    Kelly, Jack; Knottenbelt, William

    2015-01-01

    Many countries are rolling out smart electricity meters. These measure a home's total power demand. However, research into consumer behaviour suggests that consumers are best able to improve their energy efficiency when provided with itemised, appliance-by-appliance consumption information. Energy disaggregation is a computational technique for estimating appliance-by-appliance energy consumption from a whole-house meter signal. To conduct research on disaggregation algorithms, researchers require data describing not just the aggregate demand per building but also the 'ground truth' demand of individual appliances. In this context, we present UK-DALE: an open-access dataset from the UK recording Domestic Appliance-Level Electricity at a sample rate of 16 kHz for the whole-house and at 1/6 Hz for individual appliances. This is the first open access UK dataset at this temporal resolution. We recorded from five houses, one of which was recorded for 655 days, the longest duration we are aware of for any energy dataset at this sample rate. We also describe the low-cost, open-source, wireless system we built for collecting our dataset.

  17. The application of seasonal latent variable in forecasting electricity demand as an alternative method

    International Nuclear Information System (INIS)

    Sumer, Kutluk Kagan; Goktas, Ozlem; Hepsag, Aycan

    2009-01-01

    In this study, we used ARIMA, seasonal ARIMA (SARIMA) and alternatively the regression model with seasonal latent variable in forecasting electricity demand by using data that belongs to 'Kayseri and Vicinity Electricity Joint-Stock Company' over the 1997:1-2005:12 periods. This study tries to examine the advantages of forecasting with ARIMA, SARIMA methods and with the model has seasonal latent variable to each other. The results support that ARIMA and SARIMA models are unsuccessful in forecasting electricity demand. The regression model with seasonal latent variable used in this study gives more successful results than ARIMA and SARIMA models because also this model can consider seasonal fluctuations and structural breaks

  18. Evolution of industrial sector electricity demand in Costa Rica

    International Nuclear Information System (INIS)

    Fischer, Steven C.

    2005-01-01

    This note is a preliminary investigation into the relationship between the efficiency of electricity utilization in the Costa Rican industrial sector and the competitive pressures generated by the implementation of economic reforms, in particular, the progressive liberalization of international trade, in the years since the debt and economic crisis of the early 1980s. The steady, year-by-year, reduction in the rate of import tariff protection, with only temporary interruptions and reverses, has been the most consistently implemented component of the macroeconomic, trade, and financial sector reforms upon which this country has embarked over the past two decades. The note sheds some light on the nature of the general policy environment that is conductive to an efficient utilization of energy in the productive sectors and to the success of national energy efficiency promotion programs in this and other parts of the world. (Author)

  19. Hybrid Forecasting Approach Based on GRNN Neural Network and SVR Machine for Electricity Demand Forecasting

    Directory of Open Access Journals (Sweden)

    Weide Li

    2017-01-01

    Full Text Available Accurate electric power demand forecasting plays a key role in electricity markets and power systems. The electric power demand is usually a non-linear problem due to various unknown reasons, which make it difficult to get accurate prediction by traditional methods. The purpose of this paper is to propose a novel hybrid forecasting method for managing and scheduling the electricity power. EEMD-SCGRNN-PSVR, the proposed new method, combines ensemble empirical mode decomposition (EEMD, seasonal adjustment (S, cross validation (C, general regression neural network (GRNN and support vector regression machine optimized by the particle swarm optimization algorithm (PSVR. The main idea of EEMD-SCGRNN-PSVR is respectively to forecast waveform and trend component that hidden in demand series to substitute directly forecasting original electric demand. EEMD-SCGRNN-PSVR is used to predict the one week ahead half-hour’s electricity demand in two data sets (New South Wales (NSW and Victorian State (VIC in Australia. Experimental results show that the new hybrid model outperforms the other three models in terms of forecasting accuracy and model robustness.

  20. What is demand response? Contributing to secure security-of-supply at the electricity markets

    International Nuclear Information System (INIS)

    Grenaa Jensen, Stine; Skytte, Klaus; Togeby, Mikael

    2004-01-01

    There is a common understanding that demand response can reduce the total costs of electricity reliability. There has especially been a growing interest in the electricity market where high spot prices in peak periods and blackouts have recently been seen. It is not easy from the existing literature to find a common definition of demands response. Often the term demand response is used broadly without looking at the time dimension. However, it does not make sense to talk about demand response without talking about when, for how long the energy is used or saved, and at which costs. This paper surveys these subjects and set up a systematic grouping of the different characteristics of demand response. It especially looks at the time dimension. (au)

  1. Modeling of Electricity Demand for Azerbaijan: Time-Varying Coefficient Cointegration Approach

    Directory of Open Access Journals (Sweden)

    Jeyhun I. Mikayilov

    2017-11-01

    Full Text Available Recent literature has shown that electricity demand elasticities may not be constant over time and this has investigated using time-varying estimation methods. As accurate modeling of electricity demand is very important in Azerbaijan, which is a transitional country facing significant change in its economic outlook, we analyze whether the response of electricity demand to income and price is varying over time in this economy. We employed the Time-Varying Coefficient cointegration approach, a cutting-edge time-varying estimation method. We find evidence that income elasticity demonstrates sizeable variation for the period of investigation ranging from 0.48% to 0.56%. The study has some useful policy implications related to the income and price aspects of the electricity consumption in Azerbaijan.

  2. Monthly electric energy demand forecasting with neural networks and Fourier series

    International Nuclear Information System (INIS)

    Gonzalez-Romera, E.; Jaramillo-Moran, M.A.; Carmona-Fernandez, D.

    2008-01-01

    Medium-term electric energy demand forecasting is a useful tool for grid maintenance planning and market research of electric energy companies. Several methods, such as ARIMA, regression or artificial intelligence, have been usually used to carry out those predictions. Some approaches include weather or economic variables, which strongly influence electric energy demand. Economic variables usually influence the general series trend, while weather provides a periodic behavior because of its seasonal nature. This work investigates the periodic behavior of the Spanish monthly electric demand series, obtained by rejecting the trend from the consumption series. A novel hybrid approach is proposed: the periodic behavior is forecasted with a Fourier series while the trend is predicted with a neural network. Satisfactory results have been obtained, with a lower than 2% MAPE, which improve those reached when only neural networks or ARIMA were used for the same purpose. (author)

  3. Electricity deregulation, spot price patterns and demand-side management

    International Nuclear Information System (INIS)

    Li, Y.; Flynn, P.C.

    2006-01-01

    This paper examines extensive hourly or half-hourly power price data from 14 deregulated power markets. It analyzes average diurnal patterns, relationship to system load, volatility, and consistency over time. Diurnal patterns indicate the average price spread between off-peak and on-peak and weekend vs. weekday power consumption. Volatility is measured by price velocity: the average normalized hourly change in power price, calculated daily. The calculated price velocity is broken down into an expected component that arises from the diurnal pattern and an unexpected component that arises from unknown factors. The analysis reveals significant differences among markets, suggesting that demand-side management (DSM) of power consumption is far more difficult in some markets than in others. At one extreme, Spain, Britain and Scandinavia show consistent diurnal price patterns, a stable relationship between price and system load, and a low unexplained component of price volatility. A power consumer in these markets could form a reasonable expectation of a reward for DSM of elective power consumption. At the other extreme, two markets in Australia show erratic diurnal price patterns from year to year, low correlation between price and system load, and a high amount of unexpected price velocity. A power consumer in these markets would have far greater difficulty in realizing a benefit from DSM. Markets that experienced one period of very high prices without a clear external cause, such as California and Alberta, appear to have a significant longer-term erosion of public support for deregulation. (author)

  4. Impacts of Demand-Side Management on Electrical Power Systems: A Review

    Directory of Open Access Journals (Sweden)

    Hussein Jumma Jabir

    2018-04-01

    Full Text Available Electricity demand has grown over the past few years and will continue to grow in the future. The increase in electricity demand is mainly due to industrialization and the shift from a conventional to a smart-grid paradigm. The number of microgrids, renewable energy sources, plug-in electric vehicles and energy storage systems have also risen in recent years. As a result, future electricity grids have to be revamped and adapt to increasing load levels. Thus, new complications associated with future electrical power systems and technologies must be considered. Demand-side management (DSM programs offer promising solutions to these issues and can considerably improve the reliability and financial performances of electrical power systems. This paper presents a review of various initiatives, techniques, impacts and recent developments of the DSM of electrical power systems. The potential benefits derived by implementing DSM in electrical power networks are presented. An extensive literature survey on the impacts of DSM on the reliability of electrical power systems is also provided for the first time. The research gaps within the broad field of DSM are also identified to provide directions for future work.

  5. The impact of demand side management strategies in the penetration of renewable electricity

    International Nuclear Information System (INIS)

    Pina, André; Silva, Carlos; Ferrão, Paulo

    2012-01-01

    High fuel costs, increasing energy security and concerns with reducing emissions have pushed governments to invest in the use of renewable energies for electricity generation. However, the intermittence of most renewable resources when renewable energy provides a significant share of the energy mix can create problems to electricity grids, which can be minimized by energy storage systems that are usually not available or expensive. An alternative solution consists on the use of demand side management strategies, which can have the double effect of reducing electricity consumption and allowing greater efficiency and flexibility in the grid management, namely by enabling a better match between supply and demand. This work analyzes the impact of demand side management strategies in the evolution of the electricity mix of Flores Island in the Azores archipelago which is characterized by high shares of renewable energy and therefore the introduction of more renewable energy sources makes it an interesting case study for testing innovative solutions. The electricity generation system is modeled in TIMES, a software which optimizes the investment and operation of wind and hydro plants until 2020 based on scenarios for demand growth, deployment of demand response technologies in the domestic sector and promotion of behavioral changes to eliminate standby power. The results show that demand side management strategies can lead to a significant delay in the investment on new generation capacity from renewable resources and improve the operation of the existing installed capacity. -- Highlights: ► Energy efficiency can help reduce the need for investment in more renewable energy. ► Dynamic demand helps increase the use of renewable energy in low demand periods. ► Around 40% of total consumption by domestic appliances is used as dynamic demand. ► The load of domestic appliances is mainly shifted to the 5:00 to 9:00 period.

  6. Price freezes, durables and residential electricity demand - Evidence from the Greater Buenos Aires

    Energy Technology Data Exchange (ETDEWEB)

    Casarin, Ariel; Delfino, Maria Eugenia

    2010-09-15

    This paper examines the determinants of residential electricity demand in the Greater Buenos Aires between 1997 and 2006. During the second half of this period, residential tariffs remained nominally fixed, while an income boom boosted up the sales of durables. This study differs from previous works in that it explicitly considers the impact of the stock of air-conditioners on residential demand. The paper reports short- and long-run elasticities and examines the contribution of prices and durables to recent demand growth. Simulations illustrate the impact of prices and durables on future demand.

  7. Avinash-Shukla mass limit for the maximum dust mass supported against gravity by electric fields

    Science.gov (United States)

    Avinash, K.

    2010-08-01

    The existence of a new class of astrophysical objects, where gravity is balanced by the shielded electric fields associated with the electric charge on the dust, is shown. Further, a mass limit MA for the maximum dust mass that can be supported against gravitational collapse by these fields is obtained. If the total mass of the dust in the interstellar cloud MD > MA, the dust collapses, while if MD < MA, stable equilibrium may be achieved. Heuristic arguments are given to show that the physics of the mass limit is similar to the Chandrasekar's mass limit for compact objects and the similarity of these dust configurations with neutron and white dwarfs is pointed out. The effect of grain size distribution on the mass limit and strong correlation effects in the core of such objects is discussed. Possible location of these dust configurations inside interstellar clouds is pointed out.

  8. Electricity demand analysis using cointegration and ARIMA modelling: A case study of Turkey

    International Nuclear Information System (INIS)

    Erdogdu, Erkan

    2007-01-01

    In the early 2000s, the Republic of Turkey has initiated an ambitious reform program in her electricity market, which requires privatization, liberalization as well as a radical restructuring. The most controversial reason behind, or justification for, recent reforms has been the rapid electricity demand growth; that is to say, the whole reform process has been a part of the endeavors to avoid the so-called 'energy crisis'. Using cointegration analysis and autoregressive integrated moving average (ARIMA) modelling, the present article focuses on this issue by both providing an electricity demand estimation and forecast, and comparing the results with official projections. The study concludes, first, that consumers' respond to price and income changes is quite limited and therefore there is a need for economic regulation in Turkish electricity market; and second, that the current official electricity demand projections highly overestimate the electricity demand, which may endanger the development of both a coherent energy policy in general and a healthy electricity market in particular

  9. Preliminary guidelines for electricity distributor conservation and demand management activities : a guide for conservation and demand management investment

    International Nuclear Information System (INIS)

    2004-01-01

    In May 2004, electricity distributors in Ontario were asked to submit deferral accounts to the Ontario Energy Board to track expenditures on conservation and demand management initiatives. The deferral accounts must be established before the distributor could recover the costs through the next installment of the allowable return on equity in March 2004. The Board will determine the appropriateness of the actual expenditures. These guidelines offer short-term assistance to distributors in establishing conservation and demand management plans and initiatives. The following specific measures may be supported by the Board: energy efficiency; operational changes to smart control systems; load management measures which facilitate interruptible and dispatchable loads, dual fuel applications, thermal storage and demand response; fuel switching measures; programs targeted to low income and hard to reach consumers; and, distributed energy options such as tri-generation, cogeneration, ground source heat pumps, wind and biomass systems. These guidelines described the regulatory treatment of conservation and demand management investments along with cost effectiveness, allocation of costs, monitoring, evaluation, and implementation. 1 appendix

  10. Extreme daily increases in peak electricity demand: Tail-quantile estimation

    International Nuclear Information System (INIS)

    Sigauke, Caston; Verster, Andréhette; Chikobvu, Delson

    2013-01-01

    A Generalized Pareto Distribution (GPD) is used to model extreme daily increases in peak electricity demand. The model is fitted to years 2000–2011 recorded data for South Africa to make a comparative analysis with the Generalized Pareto-type (GP-type) distribution. Peak electricity demand is influenced by the tails of probability distributions as well as by means or averages. At times there is a need to depart from the average thinking and exploit information provided by the extremes (tails). Empirical results show that both the GP-type and the GPD are a good fit to the data. One of the main advantages of the GP-type is the estimation of only one parameter. Modelling of extreme daily increases in peak electricity demand helps in quantifying the amount of electricity which can be shifted from the grid to off peak periods. One of the policy implications derived from this study is the need for day-time use of electricity billing system similar to the one used in the cellular telephone/and fixed line-billing technology. This will result in the shifting of electricity demand on the grid to off peak time slots as users try to avoid high peak hour charges. - Highlights: ► Policy makers should design demand response strategies to save electricity. ► Peak electricity demand is influenced by tails of probability distributions. ► Both the GSP and the GPD are a good fit to the data. ► Accurate assessment of level and frequency of extreme load forecasts is important.

  11. The Possibility of Functioning at Maximum Power for Solar Photovoltaic - Electric Battery Systems

    Directory of Open Access Journals (Sweden)

    Chioncel Cristian Paul

    2013-01-01

    Full Text Available The paper presents the functioning of a solar photovoltaic module(PVM that debits direct to on electric battery (EB. By a good adaptingof PVM to EB, so that the no load voltage of the two components (PVMand EB are well suited, during a day the energy value can be reachednear to the maximum possible value, when the PVM functions in themaximum power point (MPP. The proposed solution is much moreeconomic than the classical: PVM + DC – DC + EB because the directcurrent - direct current power converter, is not necessary (DC - DC.

  12. Future demand in electrical power and meeting this demand, in particular with the aid of nuclear energy

    International Nuclear Information System (INIS)

    1976-07-01

    As a part of the research program in question, the study deals with meeting the electrical power demand in the FRG until the year 2000 in the best possible way with regard to costs, and evaluating the long-term technical, ecological, and economical effects resulting thereof. With the aid of a model, the construction of additional plants and the use of the FRG's power plant network, always applying economical criteria, are investigated while allowing for adequate assurance of supply. It becomes obvious that the power plants and fuels available influence a 25-year planning period. In the year 2000, nuclear energy will play a dominating role in meeting the demand, the conventional thermal power plants will be used more for coping with the above-average medium laods, while peak loads will be met, above all, by pump storage stations. (UA) [de

  13. Influencing Factors and Development Trend Analysis of China Electric Grid Investment Demand Based on a Panel Co-Integration Model

    OpenAIRE

    Jinchao Li; Lin Chen; Yuwei Xiang; Jinying Li; Dong Peng

    2018-01-01

    Electric grid investment demand analysis is significant to reasonably arranging construction funds for the electric grid and reduce costs. This paper used the panel data of electric grid investment from 23 provinces of China between 2004 and 2016 as samples to analyze the influence between electric grid investment demand and GDP, population scale, social electricity consumption, installed electrical capacity, and peak load based on co-integration tests. We find that GDP and peak load have pos...

  14. Forecasted electric power demands for the Baltimore Gas and Electric Company. Volume 1 and Volume 2. Documentation manual

    International Nuclear Information System (INIS)

    Estomin, S.L.; Beach, J.E.; Goldsmith, J.V.

    1991-05-01

    The two-volume report presents the results of an econometric forecast of peak load and electric power demand for the Baltimore Gas and Electric Company (BG ampersand E) through the year 2009. Separate energy sales models were estimated for residential sales in Baltimore City, residential sales in the BG ampersand E service area excluding Baltimore City, commercial sales, industrial sales, streetlighting sales, and Company use plus losses. Econometric equations were also estimated for electric space heating and air conditioning saturation in Baltimore City and in the remainder of the BG ampersand E service territory. In addition to the energy sales models and the electric space conditioning saturation models, econometric models of summer and winter peak demand on the BG ampersand E system were estimated

  15. Electric Boiler and Heat Pump Thermo-Electrical Models for Demand Side Management Analysis in Low Voltage Grids

    DEFF Research Database (Denmark)

    Diaz de Cerio Mendaza, Iker; Bak-Jensen, Birgitte; Chen, Zhe

    2013-01-01

    The last fifteen years many European countries have integrated large percentage of renewable energy on their electricity generation mix. In Denmark the 21.3% of the electricity consumed nowadays is produced by the wind, and it has planned to be the 50% by 2025. In order to front future challenges...... on the power system control and operation, created by this unstable way of generation, Demand Side Management turns to be a promising solution. The storage capacity from thermo-electric units, like electric boilers and heat pumps, allows operating them with certain freedom. Hence they can be employed under...... certain coordination, to actively respond to the power system fluctuations. The following paper presents two simple thermo-electrical models of an electrical boiler and an air-source CO2 heat pump system. The purpose is using them in low voltage grids analysis to assess their capacity and flexibility...

  16. Integration scenarios of Demand Response into electricity markets: Load shifting, financial savings and policy implications

    International Nuclear Information System (INIS)

    Feuerriegel, Stefan; Neumann, Dirk

    2016-01-01

    Demand Response allows for the management of demand side resources in real-time; i.e. shifting electricity demand according to fluctuating supply. When integrated into electricity markets, Demand Response can be used for load shifting and as a replacement for both control reserve and balancing energy. These three usage scenarios are compared based on historic German data from 2011 to determine that load shifting provides the highest benefit: its annual financial savings accumulate to €3.110 M for both households and the service sector. This equals to relative savings of 2.83% compared to a scenario without load shifting. To improve Demand Response integration, the proposed model suggests policy implications: reducing bid sizes, delivery periods and the time-lag between market transactions and delivery dates in electricity markets. - Highlights: •Comparison of 3 scenarios to integrate Demand Response into electricity markets. •These are: optimize procurement, offer as control reserve, avoid balancing energy. •Ex post simulation to quantify financial impact and policy implications. •Highest savings from load shifting with a cost reduction of 3%. •Model suggests reducing bid sizes, delivery periods and time lags as policy issues.

  17. Electricity demand by the commercial sector in Kuwait: an econometric analysis

    International Nuclear Information System (INIS)

    Eltony, M.N.; Hajeeh, M.

    1999-01-01

    This paper models and estimates electricity demand by the Kuwaiti commercial sector, using an error correction model. It also simulates the estimated model under three scenarios and presents an analysis of the results. The empirical results indicate that short- and long-run electricity consumption and the level of economic activity are interrelated. The forecasts show that electricity consumption varies directly with economic growth. They also suggest that an increase of 100 per cent in nominal electricity prices will lead to a reduction in commercial sector electricity demand of 45 per cent by the year 2010. The simulation of the model under the different scenarios demonstrates that the potential for energy conservation exists in the commercial sector

  18. R and D options for demand side management in Japanese electric utilities

    International Nuclear Information System (INIS)

    Yamamoto, Takahiko

    1996-01-01

    Japanese electric demand has been steadily increasing in accordance with the economic growth. However, Japanese electric utilities are facing several problems; increasing construction cost of power facilities, siting constraints and the environmental issue of greenhouse gas emissions. To overcome these problems, electric utilities have been promoting demand-side-management (DSM) activities as well as supplier-side measures, with some presently being carried out through promoting energy conservation technologies and introducing electric tariff options of specific contracts for residential/commercial and industrial consumers. Japanese electric utilities have been carrying out R and D for the future, in particular, energy storage and heat storage which contribute to the improvement of load factor. In this paper, I would like to outline the R and D options for DSM in Japan. (author)

  19. Forecasting monthly peak demand of electricity in India—A critique

    International Nuclear Information System (INIS)

    Rallapalli, Srinivasa Rao; Ghosh, Sajal

    2012-01-01

    The nature of electricity differs from that of other commodities since electricity is a non-storable good and there have been significant seasonal and diurnal variations of demand. Under such condition, precise forecasting of demand for electricity should be an integral part of the planning process as this enables the policy makers to provide directions on cost-effective investment and on scheduling the operation of the existing and new power plants so that the supply of electricity can be made adequate enough to meet the future demand and its variations. Official load forecasting in India done by Central Electricity Authority (CEA) is often criticized for being overestimated due to inferior techniques used for forecasting. This paper tries to evaluate monthly peak demand forecasting performance predicted by CEA using trend method and compare it with those predicted by Multiplicative Seasonal Autoregressive Integrated Moving Average (MSARIMA) model. It has been found that MSARIMA model outperforms CEA forecasts both in-sample static and out-of-sample dynamic forecast horizons in all five regional grids in India. For better load management and grid discipline, this study suggests employing sophisticated techniques like MSARIMA for peak load forecasting in India. - Highlights: ► This paper evaluates monthly peak demand forecasting performance by CEA. ► Compares CEA forecasts it with those predicted by MSARIMA model. ► MSARIMA model outperforms CEA forecasts in all five regional grids in India. ► Opportunity exists to improve the performance of CEA forecasts.

  20. Impacts of the 2011 Tohoku earthquake on electricity demand in Japan. State space approach

    International Nuclear Information System (INIS)

    Honjo, Keita; Ashina, Shuichi

    2017-01-01

    Some papers report that consumers' electricity saving behavior (Setsuden) after the 2011 Tohoku Earthquake resulted in the reduction of the domestic electricity demand. However, time variation of the electricity saving effect (ESE) has not yet been sufficiently investigated. In this study, we develop a state space model of monthly electricity demand using long-term data, and estimate time variation of the ESE. We also estimate time variation of CO_2 emissions caused by Setsuden. Our result clearly indicates that Setsuden after the earthquake was not temporary but became established as a habit. Between March 2011 and October 2015, the ESE on power demand ranged from 2.9% to 6.9%, and the ESE on light demand ranged from 2.6% to 9.0%. The ESE on the total electricity demand was 3.2%-7.5%. Setsuden also contributed to the reduction of CO_2 emissions, but it could not offset the emissions increase caused by the shutdown of nuclear power plants. (author)

  1. High-resolution stochastic integrated thermal–electrical domestic demand model

    International Nuclear Information System (INIS)

    McKenna, Eoghan; Thomson, Murray

    2016-01-01

    Highlights: • A major new version of CREST’s demand model is presented. • Simulates electrical and thermal domestic demands at high-resolution. • Integrated structure captures appropriate time-coincidence of variables. • Suitable for low-voltage network and urban energy analyses. • Open-source development in Excel VBA freely available for download. - Abstract: This paper describes the extension of CREST’s existing electrical domestic demand model into an integrated thermal–electrical demand model. The principle novelty of the model is its integrated structure such that the timing of thermal and electrical output variables are appropriately correlated. The model has been developed primarily for low-voltage network analysis and the model’s ability to account for demand diversity is of critical importance for this application. The model, however, can also serve as a basis for modelling domestic energy demands within the broader field of urban energy systems analysis. The new model includes the previously published components associated with electrical demand and generation (appliances, lighting, and photovoltaics) and integrates these with an updated occupancy model, a solar thermal collector model, and new thermal models including a low-order building thermal model, domestic hot water consumption, thermostat and timer controls and gas boilers. The paper reviews the state-of-the-art in high-resolution domestic demand modelling, describes the model, and compares its output with three independent validation datasets. The integrated model remains an open-source development in Excel VBA and is freely available to download for users to configure and extend, or to incorporate into other models.

  2. High Electricity Demand in the Northeast U.S.: PJM Reliability Network and Peaking Unit Impacts on Air Quality.

    Science.gov (United States)

    Farkas, Caroline M; Moeller, Michael D; Felder, Frank A; Henderson, Barron H; Carlton, Annmarie G

    2016-08-02

    On high electricity demand days, when air quality is often poor, regional transmission organizations (RTOs), such as PJM Interconnection, ensure reliability of the grid by employing peak-use electric generating units (EGUs). These "peaking units" are exempt from some federal and state air quality rules. We identify RTO assignment and peaking unit classification for EGUs in the Eastern U.S. and estimate air quality for four emission scenarios with the Community Multiscale Air Quality (CMAQ) model during the July 2006 heat wave. Further, we population-weight ambient values as a surrogate for potential population exposure. Emissions from electricity reliability networks negatively impact air quality in their own region and in neighboring geographic areas. Monitored and controlled PJM peaking units are generally located in economically depressed areas and can contribute up to 87% of hourly maximum PM2.5 mass locally. Potential population exposure to peaking unit PM2.5 mass is highest in the model domain's most populated cities. Average daily temperature and national gross domestic product steer peaking unit heat input. Air quality planning that capitalizes on a priori knowledge of local electricity demand and economics may provide a more holistic approach to protect human health within the context of growing energy needs in a changing world.

  3. Determining the effect of grain size and maximum induction upon coercive field of electrical steels

    Science.gov (United States)

    Landgraf, Fernando José Gomes; da Silveira, João Ricardo Filipini; Rodrigues-Jr., Daniel

    2011-10-01

    Although theoretical models have already been proposed, experimental data is still lacking to quantify the influence of grain size upon coercivity of electrical steels. Some authors consider a linear inverse proportionality, while others suggest a square root inverse proportionality. Results also differ with regard to the slope of the reciprocal of grain size-coercive field relation for a given material. This paper discusses two aspects of the problem: the maximum induction used for determining coercive force and the possible effect of lurking variables such as the grain size distribution breadth and crystallographic texture. Electrical steel sheets containing 0.7% Si, 0.3% Al and 24 ppm C were cold-rolled and annealed in order to produce different grain sizes (ranging from 20 to 150 μm). Coercive field was measured along the rolling direction and found to depend linearly on reciprocal of grain size with a slope of approximately 0.9 (A/m)mm at 1.0 T induction. A general relation for coercive field as a function of grain size and maximum induction was established, yielding an average absolute error below 4%. Through measurement of B50 and image analysis of micrographs, the effects of crystallographic texture and grain size distribution breadth were qualitatively discussed.

  4. Linearity of electrical impedance tomography during maximum effort breathing and forced expiration maneuvers.

    Science.gov (United States)

    Ngo, Chuong; Leonhardt, Steffen; Zhang, Tony; Lüken, Markus; Misgeld, Berno; Vollmer, Thomas; Tenbrock, Klaus; Lehmann, Sylvia

    2017-01-01

    Electrical impedance tomography (EIT) provides global and regional information about ventilation by means of relative changes in electrical impedance measured with electrodes placed around the thorax. In combination with lung function tests, e.g. spirometry and body plethysmography, regional information about lung ventilation can be achieved. Impedance changes strictly correlate with lung volume during tidal breathing and mechanical ventilation. Initial studies presumed a correlation also during forced expiration maneuvers. To quantify the validity of this correlation in extreme lung volume changes during forced breathing, a measurement system was set up and applied on seven lung-healthy volunteers. Simultaneous measurements of changes in lung volume using EIT imaging and pneumotachography were obtained with different breathing patterns. Data was divided into a synchronizing phase (spontaneous breathing) and a test phase (maximum effort breathing and forced maneuvers). The EIT impedance changes correlate strictly with spirometric data during slow breathing with increasing and maximum effort ([Formula: see text]) and during forced expiration maneuvers ([Formula: see text]). Strong correlations in spirometric volume parameters [Formula: see text] ([Formula: see text]), [Formula: see text]/FVC ([Formula: see text]), and flow parameters PEF, [Formula: see text], [Formula: see text], [Formula: see text] ([Formula: see text]) were observed. According to the linearity during forced expiration maneuvers, EIT can be used during pulmonary function testing in combination with spirometry for visualisation of regional lung ventilation.

  5. Electricity demand and storage dispatch modeling for buildings and implications for the smartgrid

    Science.gov (United States)

    Zheng, Menglian; Meinrenken, Christoph

    2013-04-01

    As an enabler for demand response (DR), electricity storage in buildings has the potential to lower costs and carbon footprint of grid electricity while simultaneously mitigating grid strain and increasing its flexibility to integrate renewables (central or distributed). We present a stochastic model to simulate minute-by-minute electricity demand of buildings and analyze the resulting electricity costs under actual, currently available DR-enabling tariffs in New York State, namely a peak/offpeak tariff charging by consumed energy (monthly total kWh) and a time of use tariff charging by power demand (monthly peak kW). We then introduce a variety of electrical storage options (from flow batteries to flywheels) and determine how DR via temporary storage may increase the overall net present value (NPV) for consumers (comparing the reduced cost of electricity to capital and maintenance costs of the storage). We find that, under the total-energy tariff, only medium-term storage options such as batteries offer positive NPV, and only at the low end of storage costs (optimistic scenario). Under the peak-demand tariff, however, even short-term storage such as flywheels and superconducting magnetic energy offer positive NPV. Therefore, these offer significant economic incentive to enable DR without affecting the consumption habits of buildings' residents. We discuss implications for smartgrid communication and our future work on real-time price tariffs.

  6. Estimation of urban residential electricity demand in China using household survey data

    International Nuclear Information System (INIS)

    Zhou, Shaojie; Teng, Fei

    2013-01-01

    This paper uses annual urban household survey data of Sichuan Province from 2007 to 2009 to estimate the income and price elasticities of residential electricity demand, along with the effects of lifestyle-related variables. The empirical results show that in the urban area of Sichuan province, the residential electricity demand is price- and income-inelastic, with price and income elasticities ranging from −0.35 to −0.50 and from 0.14 to 0.33, respectively. Such lifestyle-related variables as demographic variables, dwelling size and holdings of home appliances, are also important determinants of residential electricity demand, especially the latter. These results are robust to a variety of sensitivity tests. The research findings imply that urban residential electricity demand continues to increase with the growth of income. The empirical results have important policy implications for the Multistep Electricity Price, which been adopted in some cities and is expected to be promoted nationwide through the installation of energy-efficient home appliances. - Highlights: • We estimate price and income elasticities in China using household survey data. • The current study is the first such study in China at this level. • Both price and income are inelastic. • Behavior factors have important impact on electricity consumption

  7. The long-run price sensitivity dynamics of industrial and residential electricity demand: The impact of deregulating electricity prices

    International Nuclear Information System (INIS)

    Adom, Philip Kofi

    2017-01-01

    This study examines the demand-side of Ghana's electricity sector. We test two important related hypotheses: (1) deregulation of electricity price does not promote energy conservation, and (2) demand-price relationship is not an inverted U-shaped. The Stock and Watson dynamic OLS is used to address the so-called second-order bias. The result showed that, deregulation of electricity price in Ghana has induced behaviours that are more consistent with energy conservation improvements. The demand-price relationship is an inverted U, which suggests that there is a price range that end-users can tolerate further price rise and still increase their consumption of electricity. However, the degree of price tolerability is higher for residential consumers than industrial consumers. The simulation results showed that, further economic growth is likely to compromise energy conservation but more in the industrial sector than the residential sector. On the other hand, future crude oil price is likely to deteriorate energy conservation in the initial years after 2016, but this trend is likely to reverse after the year 2020. Pricing mechanisms are potent to induce energy conservation but inadequate. The results suggest that they should be complemented with other stringent policies such as a mandatory energy reduction policy, investment in renewables, and personalization of energy efficiency programs. - Highlights: • Studies the demand-side of the electricity sector • Deregulating electricity price promotes energy conservation • Demand-price relationship is an inverted U-shaped • Pricing policies should be combined with other energy mandatory reduction policies

  8. ON THE DEMAND DYNAMICS OF ELECTRICITY IN GHANA: DO EXOGENOUS NON-ECONOMIC VARIABLES COUNT?

    Directory of Open Access Journals (Sweden)

    Ishmael Ackah

    2014-04-01

    Full Text Available The purpose of this study is to identify and quantify the effect of endogenous and exogenous economic factors on electricity demand in Ghana. The Structural Time Series Model is employed due to its ability to capture exogenous non-economic variables. The findings reveal that education has significant effect on electricity consumption in both the short and the long run. Education has inverse relationship with electricity consumption implying that the more consumers are educated, the less electricity they consume. The study also reveals that price changes have less impact on electricity consumption in the short run and that efficiency in electricity consumption has improved since 1971 and will continue for the next twenty years. The study recommends that more public education should be carried out to enhance energy conservation and also, realistic prices should be charge for electricity consumption to allow private investment into the sector.

  9. Generation of synthetic sequences of electricity demand: Application in South Australia

    International Nuclear Information System (INIS)

    Magnano, L.; Boland, J.W.

    2007-01-01

    We have developed a model to generate synthetic sequences of half-hourly electricity demand. The generated sequences represent possible realisations of electricity load that could have occurred. Each of the components included in the model has a physical interpretation. These components are yearly and daily seasonality which were modelled using Fourier series, weekly seasonality modelled with dummy variables, and the relationship with current temperature described by polynomial functions of temperature. Finally the stochastic component was modelled with autoregressive moving average (ARMA) processes. These synthetic sequences were developed for two purposes. The first one is to use them as input data in market simulation software. The second one is to build probability distributions of the outputs to calculate probabilistic forecasts. As an application several summers of half-hourly electricity demand were generated and from them the value of demand that is not expected to be exceeded more than once in 10 years was calculated

  10. Interim report of the supply/demand committee in Electric Enterprises Council

    International Nuclear Information System (INIS)

    1982-01-01

    Following a similar report made two odd years ago, an interim report was presented concerning the outlook of electric power demand and the development target for fiscal 1990, and also the electric power demand in the year 2000 to indicate the future direction. During the past two years, the energy situation both domestic and abroad has largely changed, including energy saving practice, petroleum substitute development, etc. The aggregate demand of electric power in fiscal 1990 was estimated at 795,000 million kwh, up about 4.3 % yearly from that in fiscal 1980. The target for nuclear power generation in fiscal 1990 was put at 46 million kw (22.0 % of the total power capacity). Then in the year 2000, the nuclear power generation in terms of capacity will be about 30 % of the aggregate total. (Mori, K.)

  11. The Risk of Residential Peak Electricity Demand: A Comparison of Five European Countries

    Directory of Open Access Journals (Sweden)

    Jacopo Torriti

    2017-03-01

    Full Text Available The creation of a Europe-wide electricity market combined with the increased intermittency of supply from renewable sources calls for an investigation into the risk of aggregate peak demand. This paper makes use of a risk model to assess differences in time-use data from residential end-users in five different European electricity markets. Drawing on the Multinational Time-Use Survey database, it assesses risk in relation to the probability of electrical appliance use within households for five European countries. Findings highlight in which countries and for which activities the risk of aggregate peak demand is higher and link smart home solutions (automated load control, dynamic pricing and smart appliances to different levels of peak demand risk.

  12. Maximizing the transferred power to electric arc furnace for having maximum production

    International Nuclear Information System (INIS)

    Samet, Haidar; Ghanbari, Teymoor; Ghaisari, Jafar

    2014-01-01

    In order to increase production of an EAF (electric arc furnace) by reduction of melting time, one can increase transferred power to the EAF. In other words a certain value of energy can be transferred to the EAF in less time. The transferred power to the EAF reduces when series reactors are utilized in order to have stable arc with desired characteristics. To compensate the reduced transferred power, the secondary voltage of the EAF transformer should be increased by tap changing of the transformer. On the other hand, after any tap changing of the EAF transformer, improved arc stability is degraded. Therefore, the series reactor and EAF transformer tap changing should be simultaneously determined to achieve arc with desired characteristics. In this research, three approaches are proposed to calculate the EAF system parameters, by which the optimal set-points of the different series reactor and EAF transformer taps are determined. The electric characteristics relevant to the EAF for the all transformer and series reactor taps with and without SVC (static VAr compensator) are plotted and based on these graphs the optimal set-points are tabulated. Finally, an economic evaluation is also presented for the methods. - Highlights: • The main goal is to transfer the maximum power to electric arc furnace. • Optimal transformer and series reactor taps are determined. • Arc stability and transferred power to EAF determine the optimal performance. • An economic assessment is done and the number of increased meltings is calculated

  13. Preliminary Examination of the Supply and Demand Balance for Renewable Electricity

    Energy Technology Data Exchange (ETDEWEB)

    Swezey, B.; Aabakken, J.; Bird, L.

    2007-10-01

    In recent years, the demand for renewable electricity has accelerated as a consequence of state and federal policies and the growth of voluntary green power purchase markets, along with the generally improving economics of renewable energy development. This paper reports on a preliminary examination of the supply and demand balance for renewable electricity in the United States, with a focus on renewable energy projects that meet the generally accepted definition of "new" for voluntary market purposes, i.e., projects installed on or after January 1, 1997. After estimating current supply and demand, this paper presents projections of the supply and demand balance out to 2010 and describe a number of key market uncertainties.

  14. Considering supply and demand of electric energy in life cycle assessments - a review of current methodologies

    International Nuclear Information System (INIS)

    Rehberger, M.; Hiete, M.

    2015-01-01

    A stable power grid requires a balance between electricity supply and demand. To compensate for changes in the demand the network operator puts on or takes off power plants from the net. Peak load plants operate only at times of high electricity demand. As levels for air pollutants emissions are typically lower for peak load plants for reasons of cost-effectiveness, one could argue that a unit of electric energy consumed during peak load has always been associated with a higher environmental impact than at other times. Furthermore, renewable energy technologies, smart approaches for improving the matching between electricity consumption and supply and new products such as electric vehicles or net zero emission buildings gain in importance. In life cycle assessment (LCA) environmental impacts associated with the production and possibly transmission of electricity are most often assessed based on temporally averaged national electricity mixes as electricity flows cannot be traced back to their origin. Neither fluctuations in the supply structure nor the composition of energy supply at a certain moment or regional differences are accounted for. A literature review of approaches for handling electricity in LCA is carried out to compare strengths and weaknesses of the approaches. A better understanding and knowledge about the source of electricity at a given time and place might be valuable information for further reducing environmental impacts, e.g. by shifting electricity consumption to times with ample supply of renewables. Integrating such information into LCA will allow a fairer assessment of a variety of new products which accept a lower energy efficiency to achieve a better integration of renewables into the grid. (authors)

  15. Modeling of demand response in electricity markets : effects of price elasticity

    International Nuclear Information System (INIS)

    Banda, E.C.; Tuan, L.A.

    2007-01-01

    A design mechanism for the optimal participation of customer load in electricity markets was presented. In particular, this paper presented a modified market model for the optimal procurement of interruptible loads participating in day-ahead electricity markets. The proposed model considers the effect of price elasticity and demand-response functions. The objective was to determine the role that price elasticity plays in electricity markets. The simulation model can help the Independent System Operator (ISO) identify customers offering the lowest price of interruptible loads and load flow patterns that avoid problems associated with transmission congestion and transmission losses. Various issues associated with procurement of demand-response offerings such as advance notification, locational aspect of load, and power factor of the loads, were considered. It was shown that demand response can mitigate price volatility by allowing the ISO to maintain operating reserves during peak load periods. It was noted that the potential benefits of the demand response program would be reduced when price elasticity of demand is taken into account. This would most likely occur in actual developed open electricity markets, such as Nordpool. This study was based on the CIGRE 32-bus system, which represents the Swedish high voltage power system. It was modified for this study to include a broad range of customer characteristics. 18 refs., 2 tabs., 14 figs

  16. The effects of demand uncertainty on strategic gaming in the merit-order electricity pool market

    Science.gov (United States)

    Frem, Bassam

    In a merit-order electricity pool market, generating companies (Gencos) game with their offered incremental cost to meet the electricity demand and earn bigger market shares and higher profits. However when the demand is treated as a random variable instead of as a known constant, these Genco gaming strategies become more complex. After a brief introduction of electricity markets and gaming, the effects of demand uncertainty on strategic gaming are studied in two parts: (1) Demand modelled as a discrete random variable (2) Demand modelled as a continuous random variable. In the first part, we proposed an algorithm, the discrete stochastic strategy (DSS) algorithm that generates a strategic set of offers from the perspective of the Gencos' profits. The DSS offers were tested and compared to the deterministic Nash equilibrium (NE) offers based on the predicted demand. This comparison, based on the expected Genco profits, showed the DSS to be a better strategy in a probabilistic sense than the deterministic NE. In the second part, we presented three gaming strategies: (1) Deterministic NE (2) No-Risk (3) Risk-Taking. The strategies were then tested and their profit performances were compared using two assessment tools: (a) Expected value and standard deviation (b) Inverse cumulative distribution. We concluded that despite yielding higher profit performance under the right conjectures, Risk-Taking strategies are very sensitive to incorrect conjectures on the competitors' gaming decisions. As such, despite its lower profit performance, the No-Risk strategy was deemed preferable.

  17. A bilevel model for electricity retailers' participation in a demand response market environment

    International Nuclear Information System (INIS)

    Zugno, Marco; Morales, Juan Miguel; Pinson, Pierre; Madsen, Henrik

    2013-01-01

    Demand response programmes are seen as one of the contributing solutions to the challenges posed to power systems by the large-scale integration of renewable power sources, mostly due to their intermittent and stochastic nature. Among demand response programmes, real-time pricing schemes for small consumers are believed to have significant potential for peak-shaving and load-shifting, thus relieving the power system while reducing costs and risk for energy retailers. This paper proposes a game theoretical model accounting for the Stackelberg relationship between retailers (leaders) and consumers (followers) in a dynamic price environment. Both players in the game solve an economic optimisation problem subject to stochasticity in prices, weather-related variables and must-serve load. The model allows the determination of the dynamic price-signal delivering maximum retailer profit, and the optimal load pattern for consumers under this pricing. The bilevel programme is reformulated as a single-level MILP, which can be solved using commercial off-the-shelf optimisation software. In an illustrative example, we simulate and compare the dynamic pricing scheme with fixed and time-of-use pricing. We find that the dynamic pricing scheme is the most effective in achieving load-shifting, thus reducing retailer costs for energy procurement and regulation in the wholesale market. Additionally, the redistribution of the saved costs between retailers and consumers is investigated, showing that real-time pricing is less convenient than fixed and time-of-use price for consumers. This implies that careful design of the retail market is needed. Finally, we carry out a sensitivity analysis to analyse the effect of different levels of consumer flexibility. - Highlights: ► We model the game between electricity retailers and consumers under dynamic pricing. ► The retailer cuts procurement costs by shifting demand in time via price-incentive. ► Imbalance costs for the retailer taper

  18. A perspective on electric vehicles: cost-benefit analysis and potential demand

    International Nuclear Information System (INIS)

    2011-01-01

    This report proposes some quantitative elements to assess the large scale diffusion of electric vehicles and analyse the potential demand for such vehicles. The first part proposes a cost-benefit analysis of the development of electric vehicles based on estimated costs and expected benefits by 2020. It addresses the following issues: framework and hypothesis, total cost of ownership, costs related to the deployment of a network of recharging infrastructures, assessment of external costs, and comparative cost-benefit analysis of electric vehicles. In the second part, the authors aim at identifying a potential demand for electric vehicles from the 2008 French national transport displacement survey (ENTD 2008) which provides recent data on the mobility of the French population

  19. Estimating deficit probabilities with price-responsive demand in contract-based electricity markets

    International Nuclear Information System (INIS)

    Galetovic, Alexander; Munoz, Cristian M.

    2009-01-01

    Studies that estimate deficit probabilities in hydrothermal systems have generally ignored the response of demand to changing prices, in the belief that such response is largely irrelevant. We show that ignoring the response of demand to prices can lead to substantial over or under estimation of the probability of an energy deficit. To make our point we present an estimation of deficit probabilities in Chile's Central Interconnected System between 2006 and 2010. This period is characterized by tight supply, fast consumption growth and rising electricity prices. When the response of demand to rising prices is acknowledged, forecasted deficit probabilities and marginal costs are shown to be substantially lower

  20. The electricity supply-demand balance for the winter of 2015-2016. Synthesis - November 2015

    International Nuclear Information System (INIS)

    2015-11-01

    Twice a year, RTE publishes a forecast study of the electricity supply and demand in continental France for the summer and winter periods. The study is based on the information supplied by electric utilities concerning the expected availability of power generation means and on statistical meteorological models. Safety margins are calculated using thousands of probabilistic scenarios combining various production and consumption situations. This report is the forecast study for the winter of 2015-2016

  1. The electricity supply-demand balance for the summer of 2016 - June 2016. Synthesis

    International Nuclear Information System (INIS)

    2016-06-01

    Twice a year, RTE publishes a forecast study of the electricity supply and demand in continental France for the summer and winter periods. The study is based on the information supplied by electric utilities concerning the expected availability of power generation means and on statistical meteorological models. Safety margins are calculated using thousands of probabilistic scenarios combining various production and consumption situations. This report is the forecast study for the summer of 2016

  2. Estimating the price elasticity for demand for electricity by sector in South Africa

    Directory of Open Access Journals (Sweden)

    Roula Inglesi-Lotz

    2011-12-01

    Full Text Available This paper analyses electricity consumption patterns in South Africa in an attempt to understand and identify the roots of the current electricity crisis. This is done by investigating various economic sectors’ responses to price changes using panel data for the period 1993–2004. Positive and statistically significant price elasticities over this period were found for the transport (rail and commercial sectors while there are positive, but small and statistically insignificant responses to price changes in the agriculture and mining sectors. Only the industrial sector responded to changes in electricity prices according to theory, namely illustrating negative demand elasticities. This sector, however, dominates electricity consumption resulting in aggregate demand elasticities that are negative. These results explain, in part, the current electricity crisis. Given the historic low level of electricity prices in conjunction with, on the whole, a real price decline, i.e. price increases lower than the inflation rate; there was no major incentive to reduce electricity consumption and/or to be efficient. This result supports the notion that prices do have an important signalling effect in the economy. Hence, the electricity prices should be considered not only from an economic growth or social vantage point, but also from a supply and technocratic perspective, which includes environmental factors such as CO2-emissions. Prices should not be determined without considering the system-wide implications thereof.

  3. Behavioral aspects of regulation: A discussion on switching and demand response in Turkish electricity market

    International Nuclear Information System (INIS)

    Sirin, Selahattin Murat; Gonul, Mustafa Sinan

    2016-01-01

    Electricity sector has been transformed from state-owned monopolistic utilities to competitive markets with an aim to promote incentives for improving efficiency, reducing costs and increasing service quality to customers. One of the cardinal assumptions of the liberalized and competitive electricity markets is the rational actor, and decision-makers are assumed to make the best decisions that maximize their utility. However, a vast literature on behavioral economics has shown the weakness of economic theory in explaining and predicting individuals’ decision-making behavior. This issue is quite important for competition in electricity markets in which consumers’ preferences have a significant role. Despite its importance, this issue has almost been neglected in Turkey, which has taken major steps in electricity sector restructuring. Therefore, this paper aims to examine switching and demand response behavior in Turkish electricity market by using multiple correspondence and panel data analysis, and findings are discussed in light of the neoclassical and behavioral economics literature. Analyses’ results show that consumers’ switching and demand response behavior is consistent with the neoclassical literature to some extent; however, behavioral factors are also affecting consumers’ decisions. Furthermore, there are systemic problems that hinder effective functioning of the electricity market and restrict competition. - Highlights: • Behavioral economics can provide insights for consumer’ decisions. • Switching and demand response behavior is examined by econometric methods. • Results is consistent with the neoclassical literature to some extent • However, behavioral factors are also affecting consumers’ decisions.

  4. Spatial–Temporal Analysis of the Heat and Electricity Demand of the Swiss Building Stock

    Directory of Open Access Journals (Sweden)

    Stefan Schneider

    2017-08-01

    Full Text Available In 2015, space heating and domestic hot water production accounted for around 40% of the Swiss final energy consumption. Reaching the goals of the 2050 energy strategy will require significantly reducing this share despite the growing building stock. Renewables are numerous but subject to spatial–temporal constraints. Territorial planning of energy distribution systems enabling the integration of renewables requires having a spatial–temporal characterization of the energy demand. This paper presents two bottom-up statistical extrapolation models for the estimation of the geo-dependent heat and electricity demand of the Swiss building stock. The heat demand is estimated by means of a statistical bottom-up model applied at the building level. At the municipality level, the electricity load curve is estimated by combining socio-economic indicators with average consumption per activity and/or electric device. This approach also allows to break down the estimated electricity demand according to activity type (e.g., households, various industry, and service activities and appliance type (e.g., lighting, motor force, fridges. The total estimated aggregated demand is 94 TWh for heat and 58 TWh for electricity, which represent a deviation of 2.9 and 0.5%, respectively compared to the national energy consumption statistics. In addition, comparisons between estimated and measured electric load curves are done to validate the proposed approach. Finally, these models are used to build a geo-referred database of heat and electricity demand for the entire Swiss territory. As an application of the heat demand model, a realistic saving potential is estimated for the existing building stock; this potential could be achieved through by a deep retrofit program. One advantage of the statistical bottom-up model approach is that it allows to simulate a building stock that replicates the diversity of building demand. This point is important in order to

  5. Examining demand response, renewable energy and efficiencies to meet growing electricity needs

    International Nuclear Information System (INIS)

    Elliot, N.; Eldridge, M.; Shipley, A.M.; Laitner, J.S.; Nadel, S.; Silverstein, A.; Hedman, B.; Sloan, M.

    2007-01-01

    While Texas has already taken steps to improve its renewable energy portfolio (RPS), and its energy efficiency improvement program (EEIP), the level of savings that utilities can achieve through the EEIP can be greatly increased. This report estimated the size of energy efficiency and renewable energy resources in Texas, and suggested a range of policy options that might be adopted to further extend EEIP. Current forecasts suggest that peak demand in Texas will increase by 2.3 per cent annually from 2007-2012, a level of growth which is threatening the state's ability to maintain grid reliability at reasonable cost. Almost 70 per cent of installed generating capacity is fuelled by natural gas in Texas. Recent polling has suggested that over 70 per cent of Texans are willing support increased spending on energy efficiency. Demand response measures that may be implemented in the state include incentive-based programs that pay users to reduce their electricity consumption during specific times and pricing programs, where customers are given a price signal and are expected to moderate their electricity usage. By 2023, the widespread availability of time-varying retail electric rates and complementary communications and control methods will permanently change the nature of electricity demand in the state. At present, the integrated utilities in Texas offer a variety of direct load control and time-of-use, curtailable, and interruptible rates. However, with the advent of retail competition now available as a result of the structural unbundling of investor-owned utilities, there is less demand response available in Texas. It was concluded that energy efficiency, demand response, and renewable energy resources can meet the increasing demand for electricity in Texas over the next 15 years. 4 figs

  6. Enhancement of building operations: A successful approach towards national electrical demand management

    International Nuclear Information System (INIS)

    Al-Mulla, A.; Maheshwari, G.P.; Al-Nakib, D.; ElSherbini, A.; Alghimlas, F.; Al-Taqi, H.; Al-Hadban, Y.

    2013-01-01

    Highlights: • Enhanced building operations were applied for eight large government buildings in Kuwait. • The enhanced building operations led to demand savings of 8.90 MW during the national peak hour. • Nationwide guidelines were developed for implementing the enhanced operations in similar government buildings in Kuwait. • The peak electrical demand reduction is likely to be 488 MW by the year 2030. - Abstract: An approach for managing electrical demand through enhanced building operations in hot climates is evaluated and demonstrated in this paper. The approach focuses on implementing enhanced operations in government buildings, since they are easier to implement and administer. These enhanced operations included early reduction of cooling supply before the end of the occupancy period, improved time-of-day control after occupancy period and reduced lighting. A total of eight government buildings with different construction and system characteristics were selected for implementing these enhanced operations. These buildings have a total air-conditioning area of 4.39 × 10 5 m 2 and a combined peak electrical demand of 29.3 MW. The enhanced operations resulted in demand savings of 8.90 MW during the national peak hour. Temperatures build up inside the buildings were monitored and found to be within acceptable ranges. Guidelines for nationwide implementation in similar buildings were developed based on the results of this work. Implementation is estimated to reduce demand by 488 MW by the year 2030, which amounts to capital savings of $585 million. These projected values would be important to adopt energy efficient policies for the country. Additional reductions in energy and fuel consumption are added benefits, which would result in large financial and environmental savings to the country. Moreover, the enhanced building operations would be an important tool to avoid any blackouts by properly reducing the peak electrical demand as well as operating the

  7. Analysis of electric vehicle driver recharging demand profiles and subsequent impacts on the carbon content of electric vehicle trips

    International Nuclear Information System (INIS)

    Robinson, A.P.; Blythe, P.T.; Bell, M.C.; Hübner, Y.; Hill, G.A.

    2013-01-01

    This paper quantifies the recharging behaviour of a sample of electric vehicle (EV) drivers and evaluates the impact of current policy in the north east of England on EV driver recharging demand profiles. An analysis of 31,765 EV trips and 7704 EV recharging events, constituting 23,805 h of recharging, were recorded from in-vehicle loggers as part of the Switch EV trials is presented. Altogether 12 private users, 21 organisation individuals and 32 organisation pool vehicles were tracked over two successive six month trial periods. It was found that recharging profiles varied between the different user types and locations. Private users peak demand was in the evening at home recharging points. Organisation individual vehicles were recharged primarily upon arrival at work. Organisation pool users recharged at work and public recharging points throughout the working day. It is recommended that pay-as-you-go recharging be implemented at all public recharging locations, and smart meters be used to delay recharging at home and work locations until after 23:00 h to reduce peak demand on local power grids and reduce carbon emissions associated with EV recharging. - Highlights: • Study of EV driver recharging habits in the north east of England. • 7704 electric vehicle recharging events, comprising 23,805 h were collected. • There was minimal recharging during off- peak hours. • Free parking and electricity at point of use encouraged daytime recharging. • Need for financial incentives and smart solutions to better manage recharging demand peaks

  8. Electrical demand forecast in two different scenarios of socio-economic development

    International Nuclear Information System (INIS)

    Goni, M.R.

    1996-01-01

    A projection of electrical demand for two different scenarios is presented in the study. The study period is 1993-2010 and 1993 has been taken as base year. In this planning study MAED program was used as well as all available information from INDEC (National Statistical Body), CAMMESA (Electrical Market Company) and Ministery of Economy. The results in the base year achieved an accuracy higher than 98%. The scenarios described two different rates of growth and electrical penetration in energy uses. (author). 3 refs., 9 figs., 2 tabs

  9. Regulating electricity demand peaks for home appliances using reversible fair scheduling

    DEFF Research Database (Denmark)

    Kardaras, Georgios; Rossello Busquet, Ana; Iversen, Villy Bæk

    2010-01-01

    This paper describes a novel methodology for regulating electricity demand peaks for home appliances. To achieve this objective, we will make use of the reversible fair scheduling algorithm originally developed for telecommunication networks. The main concept behind this approach is the aggregati...

  10. Optimal wind-hydro solution for the Marmara region of Turkey to meet electricity demand

    International Nuclear Information System (INIS)

    Dursun, Bahtiyar; Alboyaci, Bora; Gokcol, Cihan

    2011-01-01

    Wind power technology is now a reliable electricity production system. It presents an economically attractive solution for the continuously increasing energy demand of the Marmara region located in Turkey. However, the stochastic behavior of wind speed in the Marmara region can lead to significant disharmony between wind energy production and electricity demand. Therefore, to overcome wind's variable nature, a more reliable solution would be to integrate hydropower with wind energy. In this study, a methodology to estimate an optimal wind-hydro solution is developed and it is subsequently applied to six typical different site cases in the Marmara region in order to define the most beneficial configuration of the wind-hydro system. All numerical calculations are based on the long-term wind speed measurements, electrical load demand and operational characteristics of the system components. -- Research highlights: → This study is the first application of a wind-hydro pumped storage system in Turkey. → The methodology developed in this study is applied to the six sites in the Marmara region of Turkey. A wind - hydro pumped storage system is proposed to meet the electric energy demand of the Marmara region.

  11. Forecasting Electricity Demand in Thailand with an Artificial Neural Network Approach

    Directory of Open Access Journals (Sweden)

    Karin Kandananond

    2011-08-01

    Full Text Available Demand planning for electricity consumption is a key success factor for the development of any countries. However, this can only be achieved if the demand is forecasted accurately. In this research, different forecasting methods—autoregressive integrated moving average (ARIMA, artificial neural network (ANN and multiple linear regression (MLR—were utilized to formulate prediction models of the electricity demand in Thailand. The objective was to compare the performance of these three approaches and the empirical data used in this study was the historical data regarding the electricity demand (population, gross domestic product: GDP, stock index, revenue from exporting industrial products and electricity consumption in Thailand from 1986 to 2010. The results showed that the ANN model reduced the mean absolute percentage error (MAPE to 0.996%, while those of ARIMA and MLR were 2.80981 and 3.2604527%, respectively. Based on these error measures, the results indicated that the ANN approach outperformed the ARIMA and MLR methods in this scenario. However, the paired test indicated that there was no significant difference among these methods at α = 0.05. According to the principle of parsimony, the ARIMA and MLR models might be preferable to the ANN one because of their simple structure and competitive performance

  12. Ensuring the security of electricity supply in Ontario: is demand-side management the answer?

    International Nuclear Information System (INIS)

    Chuddy, B.

    2004-01-01

    This paper examines the issues relating to ensuring the security of electricity supply in Ontario. In particular, it focuses on demand-side management as a means of achieving these objectives. The solution involves both conservation and supply. It is therefore critical that there be investment in new supply with multiple buyers/sellers. regulatory environment and pricing could encourage conservation

  13. Modeling and Analysis of Commercial Building Electrical Loads for Demand Side Management

    Science.gov (United States)

    Berardino, Jonathan

    In recent years there has been a push in the electric power industry for more customer involvement in the electricity markets. Traditionally the end user has played a passive role in the planning and operation of the power grid. However, many energy markets have begun opening up opportunities to consumers who wish to commit a certain amount of their electrical load under various demand side management programs. The potential benefits of more demand participation include reduced operating costs and new revenue opportunities for the consumer, as well as more reliable and secure operations for the utilities. The management of these load resources creates challenges and opportunities to the end user that were not present in previous market structures. This work examines the behavior of commercial-type building electrical loads and their capacity for supporting demand side management actions. This work is motivated by the need for accurate and dynamic tools to aid in the advancement of demand side operations. A dynamic load model is proposed for capturing the response of controllable building loads. Building-specific load forecasting techniques are developed, with particular focus paid to the integration of building management system (BMS) information. These approaches are tested using Drexel University building data. The application of building-specific load forecasts and dynamic load modeling to the optimal scheduling of multi-building systems in the energy market is proposed. Sources of potential load uncertainty are introduced in the proposed energy management problem formulation in order to investigate the impact on the resulting load schedule.

  14. Dynamic Modeling of Kosovo's Electricity Supply-Demand, Gaseous Emissions and Air Pollution

    Directory of Open Access Journals (Sweden)

    Sadik Bekteshi

    2015-09-01

    Full Text Available In this paper is described the developing of an integrated electricity supply–demand, gaseous emission and air pollution model for study of possible baseline electricity developments and available options to mitigate emissions. This model is constructed in STELLA software, which makes use of Systems Dynamics Modeling as the methodology. Several baseline scenarios have been developed from this model and a set of options of possible developments of Kosovo's Electricity Supply–Demand and Gaseous Emissions are investigated. The analysis of various scenarios results in medium growth scenarios (MGS that imply building of generation capacities and increase in participation of the electricity generation from renewable sources. MGS would be 10% of the total electricity generation and ensure sustainable development of the electricity sector. At the same time, by implementation of new technologies, this would be accompanied by reduced GHG (CO2 and NOx emissions by 60% and significant reduction for air pollutants (dust and SO2 by 40% compared to the business-as-usual (BAU case. Conclusively, obtained results show that building of new generation capacities by introducing new technologies and orientation on environmentally friendly energy sources can ensure sustainable development of the electricity sector in Kosovo.  

  15. Predicting summer residential electricity demand across the U.S.A using climate information

    Science.gov (United States)

    Sun, X.; Wang, S.; Lall, U.

    2017-12-01

    We developed a Bayesian Hierarchical model to predict monthly residential per capita electricity consumption at the state level across the USA using climate information. The summer period was selected since cooling requirements may be directly associated with electricity use, while for winter a mix of energy sources may be used to meet heating needs. Historical monthly electricity consumption data from 1990 to 2013 were used to build a predictive model with a set of corresponding climate and non-climate covariates. A clustering analysis was performed first to identify groups of states that had similar temporal patterns for the cooling degree days of each state. Then, a partial pooling model was applied to each cluster to assess the sensitivity of monthly per capita residential electricity demand to each predictor (including cooling-degree-days, gross domestic product (GDP) per capita, per capita electricity demand of previous month and previous year, and the residential electricity price). The sensitivity of residential electricity to cooling-degree-days has an identifiable geographic distribution with higher values in northeastern United States.

  16. The residential demand for electricity in Australia: an application of the bounds testing approach to cointegration

    International Nuclear Information System (INIS)

    Narayan, P.K.; Smyth, R.

    2005-01-01

    This paper reports estimates of the long- and short-run elasticities of residential demand for electricity in Australia using the bounds testing procedure to cointegration, within an autoregressive distributive lag framework. In the long run, we find that income and own price are the most important determinants of residential electricity demand, while temperature is significant some of the time and gas prices are insignificant. Our estimates of long-run income elasticity and price elasticity of demand are consistent with previous studies, although they are towards the lower end of existing estimates. As expected, the short-run elasticities are much smaller than the long-run elasticities, and the coefficients on the error-correction coefficients are small consistent with the fact that in the short-run energy appliances are fixed. (author)

  17. Predicting the electricity demand of an oil industry region on the basis of a stochastic model

    Energy Technology Data Exchange (ETDEWEB)

    Ragimova, R A; Khaykin, I Ye

    1979-01-01

    A justified decision to accept a particular development design may be made only on the basis of a scientific prediction of the basic technical and economic indicators. Used as the basic factor which impacts on the electricity demand is the total oil production and the flow of the total liquid pumped from the bowels of the earth. The initial information is statistical data about the expenditure of electricity, the oil and liquid production for 8-10 years. The existence is accepted of a direct relation between the resultive and the factorial signs. Based on a normal law of distribution of random errors, reliable probabilities are found for determining the electricity demand of an object with an assigned degree of precision. Calculations through the proposed model in the practical work of the energy services make it possible to expose the degree of quantitative influence of the basic parameters of the development of a deposit on the value of the expenditure of electricity and to justifiably predict the electricity demand for oil production.

  18. Electricity demand load forecasting of the Hellenic power system using an ARMA model

    Energy Technology Data Exchange (ETDEWEB)

    Pappas, S.Sp. [ASPETE - School of Pedagogical and Technological Education Department of Electrical Engineering Educators N. Heraklion, 141 21 Athens (Greece); Ekonomou, L.; Chatzarakis, G.E.; Skafidas, P.D. [ASPETE-School of Pedagogical and Technological Education, Department of Electrical Engineering Educators, N. Heraklion, 141 21 Athens (Greece); Karampelas, P. [Hellenic American University, IT Department, 12 Kaplanon Str., 106 80 Athens (Greece); Karamousantas, D.C. [Technological Educational Institute of Kalamata, Antikalamos, 24 100 Kalamata (Greece); Katsikas, S.K. [University of Piraeus, Department of Technology Education and Digital Systems, 150 Androutsou St., 18 532 Piraeus (Greece)

    2010-03-15

    Effective modeling and forecasting requires the efficient use of the information contained in the available data so that essential data properties can be extracted and projected into the future. As far as electricity demand load forecasting is concerned time series analysis has the advantage of being statistically adaptive to data characteristics compared to econometric methods which quite often are subject to errors and uncertainties in model specification and knowledge of causal variables. This paper presents a new method for electricity demand load forecasting using the multi-model partitioning theory and compares its performance with three other well established time series analysis techniques namely Corrected Akaike Information Criterion (AICC), Akaike's Information Criterion (AIC) and Schwarz's Bayesian Information Criterion (BIC). The suitability of the proposed method is illustrated through an application to actual electricity demand load of the Hellenic power system, proving the reliability and the effectiveness of the method and making clear its usefulness in the studies that concern electricity consumption and electricity prices forecasts. (author)

  19. Economic demand response model in liberalised electricity markets with respect to flexibility of consumers

    DEFF Research Database (Denmark)

    Sharifi, Reza; Anvari-Moghaddam, Amjad; Fathi, S. Hamid

    2017-01-01

    Before restructuring in the electricity industry, the primary decision-makers of the electricity market were deemed to be power generation and transmission companies, market regulation boards, and power industry regulators. In this traditional structure, consumers were interested in receiving...... electricity at flat rates while paying no attention to the problems of this industry. This attitude was the source of many problems, sometimes leading to collapse of power systems and widespread blackouts. Restructuring of the electricity industry however provided a multitude of solutions to these problems....... The most important solution can be demand response (DR) programs. This paper proposes an economic DR model for residential consumers in liberalized electricity markets to change their consumption pattern from times of high energy prices to other times to maximize their utility functions. This economic...

  20. Decarbonising the energy intensive basic materials industry through electrification – Implications for future EU electricity demand

    International Nuclear Information System (INIS)

    Lechtenböhmer, Stefan; Nilsson, Lars J.; Åhman, Max; Schneider, Clemens

    2016-01-01

    The need for deep decarbonisation in the energy intensive basic materials industry is increasingly recognised. In light of the vast future potential for renewable electricity the implications of electrifying the production of basic materials in the European Union is explored in a what-if thought-experiment. Production of steel, cement, glass, lime, petrochemicals, chlorine and ammonia required 125 TW-hours of electricity and 851 TW-hours of fossil fuels for energetic purposes and 671 TW-hours of fossil fuels as feedstock in 2010. The resulting carbon dioxide emissions were equivalent to 9% of total greenhouse gas emissions in EU28. A complete shift of the energy demand as well as the resource base of feedstocks to electricity would result in an electricity demand of 1713 TW-hours about 1200 TW-hours of which would be for producing hydrogen and hydrocarbons for feedstock and energy purposes. With increased material efficiency and some share of bio-based materials and biofuels the electricity demand can be much lower. Our analysis suggest that electrification of basic materials production is technically possible but could have major implications on how the industry and the electric systems interact. It also entails substantial changes in relative prices for electricity and hydrocarbon fuels. - Highlights: • Energy intensive basic materials industry has a high share in EU greenhouse gas emissions. • Decarbonising these industries is very important, but still relatively unexplored. • Electrification is possible regarding renewable energy resources and technologies. • Combination with energy and materials efficiency, biofuels and CCS is crucial. • Electrification needs very high amounts of electricity and strong policies.

  1. Generation Adequacy Report on the electricity supply-demand balance in France - 2007 Edition

    International Nuclear Information System (INIS)

    2008-01-01

    Under the terms of the Law of 10 February 2000, at least every two years, RTE (Reseau de Transport d'Electricite), working under the aegis of the Government, establishes a multi-annual Generation Adequacy Report on the electricity supply-demand balance in France. A new regulatory framework specifies the methods to be used by RTE for drawing up this independent technical expert report. The Generation Adequacy Report is one of the elements used by the Minister for Energy and the Government in general, to determine the Multi-annual Investment Programme (referred to by the French acronym PPI) for investing in energy generation facilities, introduced by the above-mentioned law. RTE publishes the report, which also appears on-line on the operator's web site www.rtefrance.com. This principle of transparency means that the information can be circulated to all the players involved in the power system and helps drive the energy debate. RTE published a previous report in 2005, which was partially updated in 2006. The Generation Adequacy Report is part of measures aimed at ensuring the security of the French electricity supply. It is intended to identify the risks of imbalances between electricity demand and the generation supply available to satisfy it over a period of around fifteen years. Consequently, it identifies the generation capacity required to meet peak demand. The choice of generation technologies to be developed, which is dictated by environmental and economic concerns, is not covered by the Generation Adequacy Report, but is a matter for the other players involved in the French electric system, and more generally, the orientations determined by the PPI. In order to carry out the analysis of the overall supply- demand balance in mainland France, RTE establishes domestic electricity demand forecasts, which it then compares with expected developments in the generating fleet

  2. Electric power demand forecasting using interval time series. A comparison between VAR and iMLP

    International Nuclear Information System (INIS)

    Garcia-Ascanio, Carolina; Mate, Carlos

    2010-01-01

    Electric power demand forecasts play an essential role in the electric industry, as they provide the basis for making decisions in power system planning and operation. A great variety of mathematical methods have been used for demand forecasting. The development and improvement of appropriate mathematical tools will lead to more accurate demand forecasting techniques. In order to forecast the monthly electric power demand per hour in Spain for 2 years, this paper presents a comparison between a new forecasting approach considering vector autoregressive (VAR) forecasting models applied to interval time series (ITS) and the iMLP, the multi-layer perceptron model adapted to interval data. In the proposed comparison, for the VAR approach two models are fitted per every hour, one composed of the centre (mid-point) and radius (half-range), and another one of the lower and upper bounds according to the interval representation assumed by the ITS in the learning set. In the case of the iMLP, only the model composed of the centre and radius is fitted. The other interval representation composed of the lower and upper bounds is obtained from the linear combination of the two. This novel approach, obtaining two bivariate models each hour, makes possible to establish, for different periods in the day, which interval representation is more accurate. Furthermore, the comparison between two different techniques adapted to interval time series allows us to determine the efficiency of these models in forecasting electric power demand. It is important to note that the iMLP technique has been selected for the comparison, as it has shown its accuracy in forecasting daily electricity price intervals. This work shows the ITS forecasting methods as a potential tool that will lead to a reduction in risk when making power system planning and operational decisions. (author)

  3. Adaptation possibilities of the nuclear electricity production to the demand; Possibilites d'adaptation de la production d'electricite nucleaires a la demande

    Energy Technology Data Exchange (ETDEWEB)

    Acket, C

    2009-02-15

    Meeting about the CO{sub 2} emissions from electric heating showed that the leak of adaptation from nuclear reactors led the use of thermal power plants (coal, petroleum, gas) to control the demand variations. This argument is analyzed in the document: is it possible to replace those thermal power plants by nuclear reactors? In this framework the author analyzes the network needs, the electricity sources and the demand answer and the specificities of the nuclear. (A.L.B.)

  4. Comparisons of recent growth in actual demand, planned demand, and planned generating capacity at U. S. electric utilities

    Energy Technology Data Exchange (ETDEWEB)

    Bopp, A.E. (James Madison Univ., Harrisonburg, VA (United States))

    1994-12-01

    During the winter of 1993, a number of U.S. electric utilities and some regional power pools discovered that current load exceeded generating capacity. Load restrictions followed, as entire regions-not just isolated utilities or even states-cut back. Was 1993 a typical, or simply a preview of the future If a preview, how did this shortage occur For a number of years, utilities, regulatory agencies, and power pools have been planning to add capacity at a much lower rate than the rate at which load has been growing. The National Electricity Reliability Council (NERC) has projected that eight of it's nine regions will have demand growth exceed capacity growth. The only region where capacity is growing faster is in the Texas Region. There are four reasons behind this shortage: excess capacity in the 1980's, disbelief in current forecasts, passage of the Clean Air act bringing stricter regulation on power plants, and the herd mentality where utilities have all delayed new plant construction.

  5. Accelerated electricity conservation in Juneau, Alaska: A study of household activities that reduced demand 25%

    International Nuclear Information System (INIS)

    Leighty, Wayne; Meier, Alan

    2011-01-01

    An avalanche destroyed the main hydroelectric transmission line to Juneau, Alaska in April, 2008. Diesel-generated electricity was substituted, causing electricity prices to increase 500% for 45 days. Electricity demand fell by 25% during the supply disruption. Most of the reduction occurred before the higher rates were implemented. Some conservation - about 8% of historic consumption - persisted after the transmission line was repaired and prices returned to normal. Consumers reduced energy use through a combination of new habits and technical improvements. A survey of residential consumers indicated that the average household undertook 10 conservation actions, with major changes in lighting, space heating, fuel switching, and water and appliance use. We propose a method for prioritizing conservation actions for promotion according to their impact in electricity savings (as a function of popularity, effectiveness, and persistence) and a dynamic framework for electricity use before, during, and after a supply disruption (i.e., both the magnitude and rates of change in electricity conservation). - Research highlights: → An electricity supply disruption caused prices to increase 500% for 45 days. → Electricity conservation of 25% occurred in a matter of days. → Electricity conservation of 8% persisted after the supply disruption was repaired. → Conservation occurred through behavior change and technology adoption. → The disruption induced consumers to try new behaviors that became new habits.

  6. Estimating the net electricity energy generation and demand using the ant colony optimization approach. Case of Turkey

    International Nuclear Information System (INIS)

    Toksari, M. Duran

    2009-01-01

    This paper presents Turkey's net electricity energy generation and demand based on economic indicators. Forecasting model for electricity energy generation and demand is first proposed by the ant colony optimization (ACO) approach. It is multi-agent system in which the behavior of each ant is inspired by the foraging behavior of real ants to solve optimization problem. Ant colony optimization electricity energy estimation (ACOEEE) model is developed using population, gross domestic product (GDP), import and export. All equations proposed here are linear electricity energy generation and demand (linear A COEEGE and linear ACOEEDE) and quadratic energy generation and demand (quadratic A COEEGE and quadratic ACOEEDE). Quadratic models for both generation and demand provided better fit solution due to the fluctuations of the economic indicators. The ACOEEGE and ACOEEDE models indicate Turkey's net electricity energy generation and demand until 2025 according to three scenarios. (author)

  7. Theoretical evaluation of maximum electric field approximation of direct band-to-band tunneling Kane model for low bandgap semiconductors

    Science.gov (United States)

    Dang Chien, Nguyen; Shih, Chun-Hsing; Hoa, Phu Chi; Minh, Nguyen Hong; Thi Thanh Hien, Duong; Nhung, Le Hong

    2016-06-01

    The two-band Kane model has been popularly used to calculate the band-to-band tunneling (BTBT) current in tunnel field-effect transistor (TFET) which is currently considered as a promising candidate for low power applications. This study theoretically clarifies the maximum electric field approximation (MEFA) of direct BTBT Kane model and evaluates its appropriateness for low bandgap semiconductors. By analysing the physical origin of each electric field term in the Kane model, it has been elucidated in the MEFA that the local electric field term must be remained while the nonlocal electric field terms are assigned by the maximum value of electric field at the tunnel junction. Mathematical investigations have showed that the MEFA is more appropriate for low bandgap semiconductors compared to high bandgap materials because of enhanced tunneling probability in low field regions. The appropriateness of the MEFA is very useful for practical uses in quickly estimating the direct BTBT current in low bandgap TFET devices.

  8. Efficient Use of Behavioral Tools to Reduce Electricity Demand of Domestic Consumers

    Directory of Open Access Journals (Sweden)

    Elbaz Shimon

    2016-12-01

    Full Text Available Purpose: The present study investigated the main literature on the subject of methods and policies for reducing the electricity demand of domestic consumers, in order to identify the place of behavioral tools. Methodology: We used secondary sources, performing a literature review, together with analysis and synthesis. Findings: Policy makers prefer to use tools offered by neoclassical economics, such as various forms of taxation, fines and financial incentives in order to make domestic electricity consumers save electricity, on the assumption that consumers will make rational decisions while maximizing their personal benefit. However, studies conducted in recent years in the field of behavioral economics, which are based on the assumption that consumers’ decisions are not rational and are affected by cognitive biases, showed that the use of behavioral tools, such as detailed online information (feedback,social comparison information, information on varying rates (dynamic pricing and general information (advertising campaign, are tools that are not less appropriate than the ones the neoclassical economics offers, mainly because electricity is an invisible product and consumers are unable to assess it by normal cognitive measures. Using an interdisciplinary combination of behavioral tools that come from a variety of approaches taken from a wide variety of different academic fields, it is possible to receive efficient results in the endeavor of reducing electricity demand. Implications: Although the neoclassical economics still remains the fundamental theory used by policymakers, it is recommended to consider behavioral economics as a complementary approach to the neoclassical economics, and combine behavioral tools in the policymakers’ toolbox, especially when those tools do not require a significant financial investment, thus efficiently maximizing the reduction of electricity demand among domestic consumers. These theoretical results will be

  9. Visualising electricity demand: use and users of a 3D chart from the 1950s

    Directory of Open Access Journals (Sweden)

    Alice Cliff

    2018-05-01

    Full Text Available Showing electricity demand by the hour, day, month and year, this 3D chart offers a rich visualisation of energy data in the UK from the years 1951–54. Acquired by the Museum of Science & Industry, Manchester, the object is significant as a tangible record of past practice, both of the electricity supply industry and its consumers. In this paper, we offer a close inspection of the object, and following its clues, we generate ideas about the chart’s use and users. In addition to commenting on the rhythmic patterning of daily and seasonal loads, we reflect on the role of the object at the time of its construction, in terms of forecasting, price-setting and load-shifting, and lobbying and demonstration. The object literally materialises electricity demand, providing a distinctive 3D representation, and in so doing prompting questions about how demand changes over time, and in time, and how our practices of everyday life constitute this demand. We conclude by offering a new interpretation of the object as a tool, as well as historical data.

  10. Energy systems scenario modelling and long term forecasting of hourly electricity demand

    Directory of Open Access Journals (Sweden)

    Poul Alberg Østergaard

    2015-06-01

    Full Text Available The Danish energy system is undergoing a transition from a system based on storable fossil fuels to a system based on fluctuating renewable energy sources. At the same time, more of and more of the energy system is becoming electrified; transportation, heating and fuel usage in industry and elsewhere. This article investigates the development of the Danish energy system in a medium year 2030 situation as well as in a long-term year 2050 situation. The analyses are based on scenario development by the Danish Climate Commission. In the short term, it is investigated what the effects will be of having flexible or inflexible electric vehicles and individual heat pumps, and in the long term it is investigated what the effects of changes in the load profiles due to changing weights of demand sectors are. The analyses are based on energy systems simulations using EnergyPLAN and demand forecasting using the Helena model. The results show that even with a limited short-term electric car fleet, these will have a significant effect on the energy system; the energy system’s ability to integrated wind power and the demand for condensing power generation capacity in the system. Charging patterns and flexibility have significant effects on this. Likewise, individual heat pumps may affect the system operation if they are equipped with heat storages. The analyses also show that the long-term changes in electricity demand curve profiles have little impact on the energy system performance. The flexibility given by heat pumps and electric vehicles in the long-term future overshadows any effects of changes in hourly demand curve profiles.

  11. Scenarios for Demand Growth of Metals in Electricity Generation Technologies, Cars, and Electronic Appliances

    Science.gov (United States)

    2018-01-01

    This study provides scenarios toward 2050 for the demand of five metals in electricity production, cars, and electronic appliances. The metals considered are copper, tantalum, neodymium, cobalt, and lithium. The study shows how highly technology-specific data on products and material flows can be used in integrated assessment models to assess global resource and metal demand. We use the Shared Socio-economic Pathways as implemented by the IMAGE integrated assessment model as a starting point. This allows us to translate information on the use of electronic appliances, cars, and renewable energy technologies into quantitative data on metal flows, through application of metal content estimates in combination with a dynamic stock model. Results show that total demand for copper, neodymium, and tantalum might increase by a factor of roughly 2 to 3.2, mostly as a result of population and GDP growth. The demand for lithium and cobalt is expected to increase much more, by a factor 10 to more than 20, as a result of future (hybrid) electric car purchases. This means that not just demographics, but also climate policies can strongly increase metal demand. This shows the importance of studying the issues of climate change and resource depletion together, in one modeling framework. PMID:29533657

  12. Assessing long-term effects of demand response policies in wholesale electricity markets

    International Nuclear Information System (INIS)

    Cepeda, Mauricio; Saguan, Marcelo

    2014-05-01

    This paper deals with the practical problems related to long-term issues in electricity markets in the presence of demand response development. Different policies have been implemented around the world aiming to develop demand response potential. Externalities, in particular the CO_2 externality, have been one of the key elements in the debate on the effectiveness of different policies regarding demand response development. Policy makers have several options to deal with this externality. The most direct one is to correct the externality by setting a CO_2 price at a level that corresponds to the cost to society of the corresponding CO_2 emissions. One alternative solution could be to subsidize carbon-free technologies as demand response. In this paper we examine potential long-term impacts of these two policies. We rely on a long-term market simulation model that characterizes expansion decisions in a competitive regime. We test for each policy two different scenarios regarding the possibility of internalization of the CO_2 externality. The results show that differences in development policies affect both investments and social costs in the wholesale electricity market and confirm previous findings that a market-driven development of demand response with the internalization of the CO_2 externality is the most efficient approach. (authors)

  13. Scenarios for Demand Growth of Metals in Electricity Generation Technologies, Cars, and Electronic Appliances.

    Science.gov (United States)

    Deetman, Sebastiaan; Pauliuk, Stefan; van Vuuren, Detlef P; van der Voet, Ester; Tukker, Arnold

    2018-04-17

    This study provides scenarios toward 2050 for the demand of five metals in electricity production, cars, and electronic appliances. The metals considered are copper, tantalum, neodymium, cobalt, and lithium. The study shows how highly technology-specific data on products and material flows can be used in integrated assessment models to assess global resource and metal demand. We use the Shared Socio-economic Pathways as implemented by the IMAGE integrated assessment model as a starting point. This allows us to translate information on the use of electronic appliances, cars, and renewable energy technologies into quantitative data on metal flows, through application of metal content estimates in combination with a dynamic stock model. Results show that total demand for copper, neodymium, and tantalum might increase by a factor of roughly 2 to 3.2, mostly as a result of population and GDP growth. The demand for lithium and cobalt is expected to increase much more, by a factor 10 to more than 20, as a result of future (hybrid) electric car purchases. This means that not just demographics, but also climate policies can strongly increase metal demand. This shows the importance of studying the issues of climate change and resource depletion together, in one modeling framework.

  14. Dealing with Demand in Electric Grids with an Adaptive Consumption Management Platform

    Directory of Open Access Journals (Sweden)

    Diego M. Jiménez-Bravo

    2018-01-01

    Full Text Available The control of consumption in homes and workplaces is an increasingly important aspect if we consider the growing popularity of smart cities, the increasing use of renewable energies, and the policies of the European Union on using energy in an efficient and clean way. These factors make it necessary to have a system that is capable of predicting what devices are connected to an electrical network. For demand management, the system must also be able to control the power supply to these devices. To this end, we propose the use of a multiagent system that includes agents with advanced reasoning and learning capacities. More specifically, the agents incorporate a case-based reasoning system and machine learning techniques. Besides, the multiagent system includes agents that are specialized in the management of the data acquired and the electrical devices. The aim is to adjust the consumption of electricity in networks to the electrical demand, and this will be done by acting automatically on the detected devices. The proposed system provides promising results; it is capable of predicting what devices are connected to the power grid at a high success rate. The accuracy of the system makes it possible to act according to the device preferences established in the system. This allows for adjusting the consumption to the current demand situation, without the risk of important home appliances being switched off.

  15. Modeling Ontario regional electricity system demand using a mixed fixed and random coefficients approach

    Energy Technology Data Exchange (ETDEWEB)

    Hsiao, C.; Mountain, D.C.; Chan, M.W.L.; Tsui, K.Y. (University of Southern California, Los Angeles (USA) McMaster Univ., Hamilton, ON (Canada) Chinese Univ. of Hong Kong, Shatin)

    1989-12-01

    In examining the municipal peak and kilowatt-hour demand for electricity in Ontario, the issue of homogeneity across geographic regions is explored. A common model across municipalities and geographic regions cannot be supported by the data. Considered are various procedures which deal with this heterogeneity and yet reduce the multicollinearity problems associated with regional specific demand formulations. The recommended model controls for regional differences assuming that the coefficients of regional-seasonal specific factors are fixed and different while the coefficients of economic and weather variables are random draws from a common population for any one municipality by combining the information on all municipalities through a Bayes procedure. 8 tabs., 41 refs.

  16. Dynamics of electricity supply and demand in Kerala: a macro econometric analysis

    Energy Technology Data Exchange (ETDEWEB)

    Pillai, P P

    1981-01-01

    Kerala has the reputation of being a surplus state in electricity, but per capita consumption (at 76 kWh compared to 130 kWh for Tamil Nadu during the same period) is one of the lowest in India. The state ranks only seventh in terms of installed capacity and is lower than the overall average of 32.12 MW per million of population. Industrial and technological development will mean that supply will be inadequate, and Kerala will have to import electricity unless corrective measures are taken. Abundant hydro-electric sources provide the state with non-polluting and inexpensive power as well as irrigation. This source must be maximized as the state promotes industry and raises its standard of living. This book analyzes Kerala's electricity supply, system efficiency, future demand, rural electrification programs, and economic development, and makes several recommendations for planning and implementing an increase in power production. 13 references, 1 figures, 34 tables.

  17. Grey prediction with rolling mechanism for electricity demand forecasting of Turkey

    International Nuclear Information System (INIS)

    Akay, Diyar; Atak, Mehmet

    2007-01-01

    The need for energy supply, especially for electricity, has been increasing in the last two decades in Turkey. In addition, owing to the uncertain economic structure of the country, electricity consumption has a chaotic and nonlinear trend. Hence, electricity configuration planning and estimation has been the most critical issue of active concern for Turkey. The Turkish Ministry of Energy and Natural Resources (MENR) has officially carried out energy planning studies using the Model of Analysis of the Energy Demand (MAED). In this paper, Grey prediction with rolling mechanism (GPRM) approach is proposed to predict the Turkey's total and industrial electricity consumption. GPRM approach is used because of high prediction accuracy, applicability in the case of limited data situations and requirement of little computational effort. Results show that proposed approach estimates more accurate results than the results of MAED, and have explicit advantages over extant studies. Future projections have also been done for total and industrial sector, respectively

  18. Maximum entropy reconstruction of poloidal magnetic field and radial electric field profiles in tokamaks

    Science.gov (United States)

    Chen, Yihang; Xiao, Chijie; Yang, Xiaoyi; Wang, Tianbo; Xu, Tianchao; Yu, Yi; Xu, Min; Wang, Long; Lin, Chen; Wang, Xiaogang

    2017-10-01

    The Laser-driven Ion beam trace probe (LITP) is a new diagnostic method for measuring poloidal magnetic field (Bp) and radial electric field (Er) in tokamaks. LITP injects a laser-driven ion beam into the tokamak, and Bp and Er profiles can be reconstructed using tomography methods. A reconstruction code has been developed to validate the LITP theory, and both 2D reconstruction of Bp and simultaneous reconstruction of Bp and Er have been attained. To reconstruct from experimental data with noise, Maximum Entropy and Gaussian-Bayesian tomography methods were applied and improved according to the characteristics of the LITP problem. With these improved methods, a reconstruction error level below 15% has been attained with a data noise level of 10%. These methods will be further tested and applied in the following LITP experiments. Supported by the ITER-CHINA program 2015GB120001, CHINA MOST under 2012YQ030142 and National Natural Science Foundation Abstract of China under 11575014 and 11375053.

  19. Artificial Neural Network Maximum Power Point Tracker for Solar Electric Vehicle

    Institute of Scientific and Technical Information of China (English)

    Theodore Amissah OCRAN; CAO Junyi; CAO Binggang; SUN Xinghua

    2005-01-01

    This paper proposes an artificial neural network maximum power point tracker (MPPT) for solar electric vehicles. The MPPT is based on a highly efficient boost converter with insulated gate bipolar transistor (IGBT) power switch. The reference voltage for MPPT is obtained by artificial neural network (ANN) with gradient descent momentum algorithm. The tracking algorithm changes the duty-cycle of the converter so that the PV-module voltage equals the voltage corresponding to the MPPT at any given insolation, temperature, and load conditions. For fast response, the system is implemented using digital signal processor (DSP). The overall system stability is improved by including a proportional-integral-derivative (PID) controller, which is also used to match the reference and battery voltage levels. The controller, based on the information supplied by the ANN, generates the boost converter duty-cycle. The energy obtained is used to charge the lithium ion battery stack for the solar vehicle. The experimental and simulation results show that the proposed scheme is highly efficient.

  20. Connecting plug-in vehicles with green electricity through consumer demand

    Science.gov (United States)

    Axsen, Jonn; Kurani, Kenneth S.

    2013-03-01

    The environmental benefits of plug-in electric vehicles (PEVs) increase if the vehicles are powered by electricity from ‘green’ sources such as solar, wind or small-scale hydroelectricity. Here, we explore the potential to build a market that pairs consumer purchases of PEVs with purchases of green electricity. We implement a web-based survey with three US samples defined by vehicle purchases: conventional new vehicle buyers (n = 1064), hybrid vehicle buyers (n = 364) and PEV buyers (n = 74). Respondents state their interest in a PEV as their next vehicle, in purchasing green electricity in one of three ways, i.e., monthly subscription, two-year lease or solar panel purchase, and in combining the two products. Although we find that a link between PEVs and green electricity is not presently strong in the consciousness of most consumers, the combination is attractive to some consumers when presented. Across all three respondent segments, pairing a PEV with a green electricity program increased interest in PEVs—with a 23% demand increase among buyers of conventional vehicles. Overall, about one-third of respondents presently value the combination of a PEV with green electricity; the proportion is much higher among previous HEV and PEV buyers. Respondents’ reported motives for interest in both products and their combination include financial savings (particularly among conventional buyers), concerns about air pollution and the environment, and interest in new technology (particularly among PEV buyers). The results provide guidance regarding policy and marketing strategies to advance PEVs and green electricity demand.

  1. Connecting plug-in vehicles with green electricity through consumer demand

    International Nuclear Information System (INIS)

    Axsen, Jonn; Kurani, Kenneth S

    2013-01-01

    The environmental benefits of plug-in electric vehicles (PEVs) increase if the vehicles are powered by electricity from ‘green’ sources such as solar, wind or small-scale hydroelectricity. Here, we explore the potential to build a market that pairs consumer purchases of PEVs with purchases of green electricity. We implement a web-based survey with three US samples defined by vehicle purchases: conventional new vehicle buyers (n = 1064), hybrid vehicle buyers (n = 364) and PEV buyers (n = 74). Respondents state their interest in a PEV as their next vehicle, in purchasing green electricity in one of three ways, i.e., monthly subscription, two-year lease or solar panel purchase, and in combining the two products. Although we find that a link between PEVs and green electricity is not presently strong in the consciousness of most consumers, the combination is attractive to some consumers when presented. Across all three respondent segments, pairing a PEV with a green electricity program increased interest in PEVs—with a 23% demand increase among buyers of conventional vehicles. Overall, about one-third of respondents presently value the combination of a PEV with green electricity; the proportion is much higher among previous HEV and PEV buyers. Respondents’ reported motives for interest in both products and their combination include financial savings (particularly among conventional buyers), concerns about air pollution and the environment, and interest in new technology (particularly among PEV buyers). The results provide guidance regarding policy and marketing strategies to advance PEVs and green electricity demand. (letter)

  2. Impact of energy storage in buildings on electricity demand side management

    International Nuclear Information System (INIS)

    Qureshi, Waqar A.; Nair, Nirmal-Kumar C.; Farid, Mohammad M.

    2011-01-01

    Research highlights: → Phase change material (PCM) application for space heating has been implemented and assessed for built environment. → Real-Time Pricing (RTP) is assessed as tool to implement Demand Side Management programs effectively. → Two buildings, with and without PCM, have been compared for space heating using RTP in functional electricity market. → PCM found to offer peak load shifting, energy conservation, and reduction in price of electricity. -- Abstract: This paper assesses impact of using phase change materials (PCM) in buildings to leverage its thermal energy storage capability. The emphasis is from an electricity demand side perspective with case studies that incorporates wholesale electricity market data of New Zealand. The results presented in this paper show that for space heating application significant advantages could be obtained using PCM built structures. These positive impacts include peak load shifting, energy conservation and reduction in peak demand for network line companies and potential reduction in electricity consumption and savings for residential customers. This paper uses a testing facility that consists of two identically designed and shaped offices built at Tamaki Campus location of the University of Auckland, New Zealand. The walls and ceilings of one office are finished with ordinary gypsum boards while the interior of the other office is finished with PCM impregnated gypsum boards. Controlled heating facility is provided in both the offices for maintaining temperature within the range of human comfort. This facility is equipped with advanced data acquisition equipment for data monitoring and archiving both locally within the offices and also remotely. Through actual observations and analysis this paper demonstrates two major impacts of DSM. First, the application of phase change material (PCM) in building environment enabling efficient thermal storage to achieve some reduction in the overall electrical energy

  3. Climate Change Impacts on Electricity Demand and Supply in the United States: A Multi-Model Comparison

    Science.gov (United States)

    This paper compares the climate change impacts on U.S. electricity demand and supply from three models: the Integrated Planning Model (IPM), the Regional Energy Deployment System (ReEDS) model, and GCAM. Rising temperatures cause an appreciable net increase in electricity demand....

  4. Electricity Consumption Forecasting Scheme via Improved LSSVM with Maximum Correntropy Criterion

    OpenAIRE

    Jiandong Duan; Xinyu Qiu; Wentao Ma; Xuan Tian; Di Shang

    2018-01-01

    In recent years, with the deepening of China’s electricity sales side reform and electricity market opening up gradually, the forecasting of electricity consumption (FoEC) becomes an extremely important technique for the electricity market. At present, how to forecast the electricity accurately and make an evaluation of results scientifically are still key research topics. In this paper, we propose a novel prediction scheme based on the least-square support vector machine (LSSVM) model with a...

  5. R and D options for demand side management in Japanese electric utilities

    International Nuclear Information System (INIS)

    Yamamoto, T.

    1995-01-01

    Japanese electric utilities are facing several problems: increasing construction cost of power facilities, siting constraints and the environmental issue of greenhouse gas emissions. To overcome these problems, electric utilities have been promoting demand-side-management (DSM) activities as well as supplier-side measures, with some presently being carried out through promoting energy conservation technologies and introducing tariff options for residential/commercial and industrial consumers. R and D works have been carried out on various fields such as energy storage and heat storage which contribute to the improvement of the load factor. 5 figs., 2 tabs

  6. Modelling changes to electricity demand load duration curves as a consequence of predicted climate change for Australia

    International Nuclear Information System (INIS)

    Thatcher, Marcus J.

    2007-01-01

    In this paper, we describe a method for constructing regional electricity demand data sets at 30 min intervals, which are consistent with climate change scenarios. Specifically, we modify a commonly used linear regression model between regional electricity demand and climate to also describe intraday variability in demand so that regional load duration curves (LDCs) can be predicted. The model is evaluated for four different Australian states that are participants in the Australian National Electricity Market (NEM) and the resultant data sets are found to reproduce each state's LDCs with reasonable accuracy. We also apply the demand model to CSIRO's Mk 3 global climate model data sets that have been downscaled to 60 km resolution using CSIRO's conformal-cubic atmospheric model to estimate how LDCs change as a consequence of a 1 C increase in the average temperature of Australian state capital cities. These regional electricity demand data sets are then useful for economic modelling of electricity markets such as the NEM. (author)

  7. Generation adequacy report on the electricity supply-demand balance in France - 2012 edition

    International Nuclear Information System (INIS)

    2012-01-01

    After an introduction presenting the objective of this report and the method used for the forecasts, this document proposes, first, an analysis of the medium-term evolution of: 1 - electricity consumption (past trends, medium-term perspectives, medium-term consumption scenarios); 2 - electricity supply (nuclear production, centralised and decentralised production from fossil-fueled power plants, hydro-power, wind-power and photovoltaic production, peak-load management); 3 - supply and demand balance (probabilistic approach, reference scenario, scenario sensitivity with respect to the demand). Then it presents the long-term determining factors (socio-economic context, energy efficiency, energy mix, interconnected grids development) and the long-term prospective scenarios (medium- and strong-consumption, new-mix, low growth). Finally, a summary and a comparison with the 2011 report is made

  8. Future Electricity Demand of the Emerging European Countries and the CIS Countries

    Directory of Open Access Journals (Sweden)

    Mehmet Fatih Bayramoglu

    2016-10-01

    Full Text Available Nowadays, one of the leading factors used in the evaluation of a country’s economic development is energy consumption. Because of economic growth, demand for energy is also increasing. In this study, the emerging European countries’ (the Czech Republic, Poland, Romania, Turkey and the CIS countries’ (Kazakhstan, Russia, Ukraine, Uzbekistan  electricity consumption has been forecasted for five years period (2015-2019. In the study, GM(1,1 Rolling Model, which is developed in the framework of Grey System Theory is used as a mathematical model for real-time forecasting. The results of the study show that there will not be a significant change in electricity demand in this two area during the 2015-2109 period.

  9. Medium- and long-term electric power demand forecasting based on the big data of smart city

    Science.gov (United States)

    Wei, Zhanmeng; Li, Xiyuan; Li, Xizhong; Hu, Qinghe; Zhang, Haiyang; Cui, Pengjie

    2017-08-01

    Based on the smart city, this paper proposed a new electric power demand forecasting model, which integrates external data such as meteorological information, geographic information, population information, enterprise information and economic information into the big database, and uses an improved algorithm to analyse the electric power demand and provide decision support for decision makers. The data mining technology is used to synthesize kinds of information, and the information of electric power customers is analysed optimally. The scientific forecasting is made based on the trend of electricity demand, and a smart city in north-eastern China is taken as a sample.

  10. Response of residential electricity demand to price: The effect of measurement error

    International Nuclear Information System (INIS)

    Alberini, Anna; Filippini, Massimo

    2011-01-01

    In this paper we present an empirical analysis of the residential demand for electricity using annual aggregate data at the state level for 48 US states from 1995 to 2007. Earlier literature has examined residential energy consumption at the state level using annual or monthly data, focusing on the variation in price elasticities of demand across states or regions, but has failed to recognize or address two major issues. The first is that, when fitting dynamic panel models, the lagged consumption term in the right-hand side of the demand equation is endogenous. This has resulted in potentially inconsistent estimates of the long-run price elasticity of demand. The second is that energy price is likely mismeasured. To address these issues, we estimate a dynamic partial adjustment model using the Kiviet corrected Least Square Dummy Variables (LSDV) (1995) and the Blundell-Bond (1998) estimators. We find that the long-term elasticities produced by the Blundell-Bond system GMM methods are largest, and that from the bias-corrected LSDV are greater than that from the conventional LSDV. From an energy policy point of view, the results obtained using the Blundell-Bond estimator where we instrument for price imply that a carbon tax or other price-based policy may be effective in discouraging residential electricity consumption and hence curbing greenhouse gas emissions in an electricity system mainly based on coal and gas power plants. - Research Highlights: → Updated information on price elasticities for the US energy policy. → Taking into account measurement error in the price variable increase price elasticity. → Room for discouraging residential electricity consumption using price increases.

  11. Asheville, North Carolina: Reducing Electricity Demand through Building Programs & Policies (City Energy: From Data to Decisions)

    Energy Technology Data Exchange (ETDEWEB)

    Office of Strategic Programs, Strategic Priorities and Impact Analysis Team

    2017-09-29

    This fact sheet "Asheville, North Carolina: Reducing Electricity Demand through Building Programs & Policies" explains how the City of Asheville used data from the U.S. Department of Energy's Cities Leading through Energy Analysis and Planning (Cities-LEAP) and the State and Local Energy Data (SLED) programs to inform its city energy planning. It is one of ten fact sheets in the "City Energy: From Data to Decisions" series.

  12. Response of residential electricity demand to price: The effect of measurement error

    Energy Technology Data Exchange (ETDEWEB)

    Alberini, Anna [Department of Agricultural Economics, University of Maryland (United States); Centre for Energy Policy and Economics (CEPE), ETH Zurich (Switzerland); Gibson Institute and Institute for a Sustainable World, School of Biological Sciences, Queen' s University Belfast, Northern Ireland (United Kingdom); Filippini, Massimo, E-mail: mfilippini@ethz.ch [Centre for Energy Policy and Economics (CEPE), ETH Zurich (Switzerland); Department of Economics, University of Lugano (Switzerland)

    2011-09-15

    In this paper we present an empirical analysis of the residential demand for electricity using annual aggregate data at the state level for 48 US states from 1995 to 2007. Earlier literature has examined residential energy consumption at the state level using annual or monthly data, focusing on the variation in price elasticities of demand across states or regions, but has failed to recognize or address two major issues. The first is that, when fitting dynamic panel models, the lagged consumption term in the right-hand side of the demand equation is endogenous. This has resulted in potentially inconsistent estimates of the long-run price elasticity of demand. The second is that energy price is likely mismeasured. To address these issues, we estimate a dynamic partial adjustment model using the Kiviet corrected Least Square Dummy Variables (LSDV) (1995) and the Blundell-Bond (1998) estimators. We find that the long-term elasticities produced by the Blundell-Bond system GMM methods are largest, and that from the bias-corrected LSDV are greater than that from the conventional LSDV. From an energy policy point of view, the results obtained using the Blundell-Bond estimator where we instrument for price imply that a carbon tax or other price-based policy may be effective in discouraging residential electricity consumption and hence curbing greenhouse gas emissions in an electricity system mainly based on coal and gas power plants. - Research Highlights: > Updated information on price elasticities for the US energy policy. > Taking into account measurement error in the price variable increase price elasticity. > Room for discouraging residential electricity consumption using price increases.

  13. Bulk electric system reliability evaluation incorporating wind power and demand side management

    Science.gov (United States)

    Huang, Dange

    correlations and the interactive effects of wind power and load forecast uncertainty on system reliability are examined. The concept of the security cost associated with operating in the marginal state in the well-being framework is incorporated in the economic analyses associated with system expansion planning including wind power and load forecast uncertainty. Overall reliability cost/worth analyses including security cost concepts are applied to select an optimal wind power injection strategy in a bulk electric system. The effects of the various demand side management measures on system reliability are illustrated using the system, load point, and well-being indices, and the reliability index probability distributions. The reliability effects of demand side management procedures in a bulk electric system including wind power and load forecast uncertainty considerations are also investigated. The system reliability effects due to specific demand side management programs are quantified and examined in terms of their reliability benefits.

  14. Modeling sustainable long-term electricity supply-demand in Africa

    International Nuclear Information System (INIS)

    Ouedraogo, Nadia S.

    2017-01-01

    Highlights: • This study is one of the first detailed and complete representation of the African power system. • It models, within LEAP, possible future paths for the regional power systems. • All the end-users and supply side activities and actors are considered. • Three scenarios are examined: the baseline, the renewable energy, and the energy efficiency. • The energy efficiency scenario has allowed to draw a sustainable pathway for electrification. - Abstract: This paper develops a scenario-based model to identify and provide an array of electricity demand in Africa, and to derive them from the African power system of development. A system-based approach is performed by applying the scenario methodology developed by Schwartz in the context of the energy-economic modeling platform ‘Long-range Energy Alternative Planning’. Four scenarios are investigated. The Business as Usual scenario (BAU) replicates the regional and national Master Plans. The renewable-promotion scenario increases the share of renewable energy in the electricity mix. The demand and supply side efficiency scenarios investigate the impact of energy efficiency measures on the power system. The results show an increase in electricity demand by 4% by 2040, supply shortages and high emissions of Greenhouse Gases. Contrary to expectations, the renewable energy scenario did not emerge as the best solution to a sustainable electrification of the region. The energy efficiency scenarios have allowed us to draw a sustainable pathway for electrification.

  15. A demand/supply and price outlook for electricity in Ontario

    International Nuclear Information System (INIS)

    Dalton, J.

    2004-01-01

    This paper examined electricity pricing issues for both the immediate future as well as over the long term. The near term outlook resources for the summer of 2004 were reviewed. Intermediate critical supply and demand issues were projected with consideration given to the return of the Pickering A plant and coal phase out. In the long term, it was considered that pricing and demand would reflect conservation issues and demand side response, as well as the timing of Requests For Proposals (RFPs) and the phase out of coal-fired capacity. The impact of the coal phase-out in Ontario was examined, with particular reference to timing and market structure implications. Potential conservation impacts were presented and projected Ontario supply/demand balances were evaluated. The challenges facing the new market structure include pricing dynamics and a reliance on RFPs. The significance of specifying diversity objectives was also discussed. It was concluded that the Ontario Ministry of Energy should play a role in establishing targets for conservation, renewable energy and the overall supply of electricity. Rigorous analysis is necessary before specifying targets in terms of hydroelectric and nuclear generation as opposed to non-fossil generation. tabs., figs

  16. Reducing Energy Demand Using Wheel-Individual Electric Drives to Substitute EPS-Systems

    Directory of Open Access Journals (Sweden)

    Jürgen Römer

    2018-01-01

    Full Text Available The energy demand of vehicles is influenced, not only by the drive systems, but also by a number of add-on systems. Electric vehicles must satisfy this energy demand completely from the battery. Hence, the use of power steering systems directly result in a range reduction. The “e2-Lenk” joint project funded by the German Federal Ministry of Education and Research (BMBF involves a novel steering concept for electric vehicles to integrate the function of steering assistance into the drive-train. Specific distribution of driving torque at the steered axle allows the steering wheel torque to be influenced to support the steering force. This provides a potential for complete substitution of conventional power steering systems and reduces the vehicle’s energy demand. This paper shows the potential of wheel-individual drives influencing the driver’s steering torque using a control technique based on classical EPS control plans. Compared to conventional power-assisted steering systems, a reduced energy demand becomes evident over a wide range of operating conditions.

  17. Impacts of demand response and renewable generation in electricity power market

    Science.gov (United States)

    Zhao, Zhechong

    This thesis presents the objective of the research which is to analyze the impacts of uncertain wind power and demand response on power systems operation and power market clearing. First, in order to effectively utilize available wind generation, it is usually given the highest priority by assigning zero or negative energy bidding prices when clearing the day-ahead electric power market. However, when congestion occurs, negative wind bidding prices would aggravate locational marginal prices (LMPs) to be negative in certain locations. A load shifting model is explored to alleviate possible congestions and enhance the utilization of wind generation, by shifting proper amount of load from peak hours to off peaks. The problem is to determine proper amount of load to be shifted, for enhancing the utilization of wind generation, alleviating transmission congestions, and making LMPs to be non-negative values. The second piece of work considered the price-based demand response (DR) program which is a mechanism for electricity consumers to dynamically manage their energy consumption in response to time-varying electricity prices. It encourages consumers to reduce their energy consumption when electricity prices are high, and thereby reduce the peak electricity demand and alleviate the pressure to power systems. However, it brings additional dynamics and new challenges on the real-time supply and demand balance. Specifically, price-sensitive DR load levels are constantly changing in response to dynamic real-time electricity prices, which will impact the economic dispatch (ED) schedule and in turn affect electricity market clearing prices. This thesis adopts two methods for examining the impacts of different DR price elasticity characteristics on the stability performance: a closed-loop iterative simulation method and a non-iterative method based on the contraction mapping theorem. This thesis also analyzes the financial stability of DR load consumers, by incorporating

  18. Generation Adequacy Report on the electricity supply-demand balance in France. 2009 Edition

    International Nuclear Information System (INIS)

    2010-01-01

    Under the terms of the Law of February 10, 2000, RTE (Reseau de Transport d'Electricite), working under the aegis of the Public Authorities, periodically establishes a multi-annual forecast report on the balance of electricity supply and demand in France. The Generation Adequacy Report is one basis for the Minister for Energy, and the Public Authorities in general, to build the Multi-annual Investment Plan (referred to in this document by its French acronym PPI for Programmation Pluri-annuelle des Investissements) for electricity generation facilities, introduced by the above-mentioned law. The Generation Adequacy Report deals with the security of the French electricity supply. It intends to identify over a period of about fifteen years the risks of imbalances in continental France between the electricity demand and the generation capacity available to supply it. It enables the identification of the generation capacity required to meet the peaks of demand. The choice of generation technologies to be developed, which is dictated by environmental and economic concerns, is not covered by the Generation Adequacy Report, but is a matter for the other stakeholders in the French electric system, under the guidelines determined by the PPI. The Generation Adequacy Report is published by RTE on its web site and thus accessible to all to serve transparency and contribute to the French energy debate. This document is the fourth edition of the Generation Adequacy Report published by RTE, following its 2003, 2005 and 2007 editions. RTE publishes partial updates in-between to reflect developments in generation capacity. The last update was published in 2008. The time horizon of the 2009 edition of the Generation Adequacy Report is 2025

  19. Generation adequacy report 2009 on the electricity supply - demand balance in France

    International Nuclear Information System (INIS)

    2009-01-01

    Under the terms of the Law of February 10, 2000, RTE (Reseau de Transport d'Electricite), working under the aegis of the Public Authorities, periodically establishes a multi-annual forecast report on the balance of electricity supply and demand in France. The Generation Adequacy Report is one basis for the Minister for Energy, and the Public Authorities in general, to build the Multi-annual Investment Plan (referred to in this document by its French acronym PPI for Programmation Pluri-annuelle des Investissements) for electricity generation facilities, introduced by the above-mentioned law. The Generation Adequacy Report deals with the security of the French electricity supply. It intends to identify over a period of about fifteen years the risks of imbalances in continental France between the electricity demand and the generation capacity available to supply it. It enables the identification of the generation capacity required to meet the peaks of demand. The choice of generation technologies to be developed, which is dictated by environmental and economic concerns, is not covered by the Generation Adequacy Report, but is a matter for the other stakeholders in the French electric system, under the guidelines determined by the PPI. The Generation Adequacy Report is published by RTE on its web site and thus accessible to all to serve transparency and contribute to the French energy debate. This document is the fourth edition of the Generation Adequacy Report published by RTE, following its 2003, 2005 and 2007 editions. RTE publishes partial updates in-between to reflect developments in generation capacity. The last update was published in 2008. The time horizon of the 2009 edition of the Generation Adequacy Report is 2025. (author)

  20. A weather regime characterisation of Irish wind generation and electricity demand in winters 2009–11

    Science.gov (United States)

    Cradden, Lucy C.; McDermott, Frank

    2018-05-01

    Prolonged cold spells were experienced in Ireland in the winters of 2009–10 and 2010–11, and electricity demand was relatively high at these times, whilst wind generation capacity factors were low. Such situations can cause difficulties for an electricity system with a high dependence on wind energy. Studying the atmospheric conditions associated with these two winters offers insights into the large-scale drivers for cold, calm spells, and helps to evaluate if they are rare events over the long-term. The influence of particular atmospheric patterns on coincidental winter wind generation and weather-related electricity demand is investigated here, with a focus on blocking in the North Atlantic/European sector. The occurrences of such patterns in the 2009–10 and 2010–11 winters are examined, and 2010–11 in particular was found to be unusual in a long-term context. The results are discussed in terms of the relevance to long-term planning and investment in the electricity system.

  1. Optimal and Learning-Based Demand Response Mechanism for Electric Water Heater System

    Directory of Open Access Journals (Sweden)

    Bo Lin

    2017-10-01

    Full Text Available This paper investigates how to develop a learning-based demand response approach for electric water heater in a smart home that can minimize the energy cost of the water heater while meeting the comfort requirements of energy consumers. First, a learning-based, data-driven model of an electric water heater is developed by using a nonlinear autoregressive network with external input (NARX using neural network. The model is updated daily so that it can more accurately capture the actual thermal dynamic characteristics of the water heater especially in real-life conditions. Then, an optimization problem, based on the NARX water heater model, is formulated to optimize energy management of the water heater in a day-ahead, dynamic electricity price framework. A genetic algorithm is proposed in order to solve the optimization problem more efficiently. MATLAB (R2016a is used to evaluate the proposed learning-based demand response approach through a computational experiment strategy. The proposed approach is compared with conventional method for operation of an electric water heater. Cost saving and benefits of the proposed water heater energy management strategy are explored.

  2. Simulation of demand side participation in Spanish short term electricity markets

    International Nuclear Information System (INIS)

    Valencia-Salazar, I.; Alvarez, C.; Escriva-Escriva, G.; Alcazar-Ortega, M.

    2011-01-01

    Highlights: → Benefits from customer active participation can be obtained with a proper generation of bids and offers. → Simulation of Spanish customers' participation is shown in daily, intra-daily and balancing markets. → Market efficiency and economics profits arise in balancing markets by using customer load reductions. → Real market prices and real customers' consumptions profiles are used in the simulations. -- Abstract: Demand response resources management is one of the most investigated solutions oriented to improve the efficiency in electricity markets. In this paper, the capability of customers to participate in short term markets is analyzed. An available methodology to analyze the daily and monthly energy consumptions of large customers is used to create energy offers and bids. This allows customers to participate in energy markets in order to buy, as first step, the usual electricity consumption and, additionally, to offer demand reductions in the short term electricity markets. Additionally, this paper shows the customer potential to participate in the Spanish electricity markets.

  3. Clean coal technology choices relating to the future supply and demand of electricity in Southern Africa

    International Nuclear Information System (INIS)

    Lennon, S.J.

    1997-01-01

    The finalization of the United Nations Framework Convention on Climate Change (UNFCCC) has catalysed a high degree of debate and interest in the future of coal-fired power generation. Fossil fuel combustion is responsible for a significant percentage of pollutants emitted globally, and coal will continue to play a major role in the energy portfolios of many countries. This is particularly true for developing countries. This fact has resulted in a major focus on technologies which improve the efficiency of coal combustion and conversion to electrical energy, as well as technologies which directly of indirectly reduce overall emissions. The issues around clean coal technologies (CCT) and their evolution, development and uptake in both developed and developing countries are complex. This paper addresses these issues in a Southern African context, viewed from the policy perspective of developing countries and presented in a framework of electricity supply and demand considerations in the region. The principal climate change policy elements proposed for South Africa are presented in the context of the current electricity supply and demand situation in the region. These are presented in the context of Eskom's Integrated Electricity Planning (IEP) process including the environmental considerations inherent in decision-making processes. The potential future of the CCT, barriers to their introduction and potential measures to facilitate their accelerated adoption are discussed. (author). 4 refs., 5 tabs., 2 figs

  4. Norwegian residential electricity demand - a microeconomic assessment of the growth from 1976 to 1993

    International Nuclear Information System (INIS)

    Halvorsen, B.; Larsen, B.M.

    2001-01-01

    The Norwegian residential electricity consumption increased by an average of 3% annually during the period 1976-1993. Political signals indicate that the growth in Norwegian residential energy consumption should be reduced, and that it may be necessary to increase energy taxes. Based on data for the sample of households from the annual consumer expenditure survey, we study factors that are of importance explaining the growth in Norwegian residential electricity demand during this period. Nearly half of the growth is due to an increase in the number of households, while the rest reflects an increase in average consumption per household. The increase in average consumption per household is due to an increasing number of households possessing electric household appliances such as dryers and dishwashers, an increase in real disposable household income and in the floor space of dwellings. (author)

  5. Contrasting electricity demand with wind power supply: case study in Hungary

    International Nuclear Information System (INIS)

    Kiss, P.; Janosi, I. M.; Varga, L.

    2009-01-01

    We compare the demand of a large electricity consumer with supply given by wind farms installed at two distant geographic locations. Obviously such situation is rather unrealistic, however our main goal is a quantitative characterization of the intermittency of wind electricity. The consumption pattern consists of marked daily and weekly cycles interrupted by periods of holidays. In contrast, wind electricity production has neither short-time nor seasonal periodicities. We show that wind power integration over a restricted area cannot provide a stable base load supply, independently of the excess capacity. Further essential result is that the statistics are almost identical for a weekly periodic pattern of consumption and a constant load of the same average value. The length of both adequate supply and shortfall intervals exhibits a scale-free (power-law) frequency distribution, possible consequences are shortly discussed. (author)

  6. Contrasting Electricity Demand with Wind Power Supply: Case Study in Hungary

    Directory of Open Access Journals (Sweden)

    Imre M. Jánosi

    2009-09-01

    Full Text Available We compare the demand of a large electricity consumer with supply given by wind farms installed at two distant geographic locations. Obviously such situation is rather unrealistic, however our main goal is a quantitative characterization of the intermittency of wind electricity. The consumption pattern consists of marked daily and weekly cycles interrupted by periods of holidays. In contrast, wind electricity production has neither short-time nor seasonal periodicities. We show that wind power integration over a restricted area cannot provide a stable baseload supply, independently of the excess capacity. Further essential result is that the statistics are almost identical for a weekly periodic pattern of consumption and a constant load of the same average value. The length of both adequate supply and shortfall intervals exhibits a scale-free (power-law frequency distribution, possible consequences are shortly discussed.

  7. Power System Transient Stability Improvement Using Demand Side Management in Competitive Electricity Markets

    DEFF Research Database (Denmark)

    Hu, Weihao; Wang, Chunqi; Chen, Zhe

    2012-01-01

    Since the hourly spot market price is available one day ahead in Denmark, the price could be transferred to the consumers and they may shift some of their loads from high price periods to the low price periods in order to save their energy costs. The optimal load response to an electricity price...... for demand side management generates different load profiles and may provide an opportunity to improve the transient stability of power systems with high wind power penetrations. In this paper, the idea of the power system transient stability improvement by using optimal load response to the electricity...... price is proposed. A 102-bus power system which represents a simplified model of the western Danish power system is chosen as the study case. Simulation results show that the optimal load response to electricity prices is an effective measure to improve the power system transient stability with high...

  8. Influencing Factors and Development Trend Analysis of China Electric Grid Investment Demand Based on a Panel Co-Integration Model

    Directory of Open Access Journals (Sweden)

    Jinchao Li

    2018-01-01

    Full Text Available Electric grid investment demand analysis is significant to reasonably arranging construction funds for the electric grid and reduce costs. This paper used the panel data of electric grid investment from 23 provinces of China between 2004 and 2016 as samples to analyze the influence between electric grid investment demand and GDP, population scale, social electricity consumption, installed electrical capacity, and peak load based on co-integration tests. We find that GDP and peak load have positive influences on electric grid investment demand, but the impact of population scale, social electricity consumption, and installed electrical capacity on electric grid investment is not remarkable. We divide different regions in China into the eastern region, central region, and western region to analyze influence factors of electric grid investment, finally obtaining key factors in the eastern, central, and western regions. In the end, according to the analysis of key factors, we make a prediction about China’s electric grid investment for 2020 in different scenarios. The results offer a certain understanding for the development trend of China’s electric grid investment and contribute to the future development of electric grid investment.

  9. Consumer behavior in renewable electricity: Can branding in accordance with identity signaling increase demand for renewable electricity and strengthen supplier brands?

    International Nuclear Information System (INIS)

    Hanimann, Raphael; Vinterbäck, Johan; Mark-Herbert, Cecilia

    2015-01-01

    A higher percentage of energy from renewable resources is an important goal on many environmental policy agendas. Yet, the demand for renewable electricity in liberalized markets has developed much more slowly than the demand for other green products. To date, research has mainly examined the willingness to pay for renewable electricity, but limited research has been conducted on the motivations behind it. The concept of identity signaling has proven to play a significant role in consumer behavior for green products. However, (renewable) electricity in the Swedish residential market typically lacks two important drivers for identity signaling: visibility and product involvement. A consumer choice simulation among 434 Swedish households compared consumer choices for renewable electricity contracts. The results show a positive effect of identity signaling on the demand for renewable electricity and yield suggestions for increasing the share of renewable electricity without market distorting measures. This leads to implications for policymakers, electricity suppliers and researchers. - Highlights: • Low demand for renewable electricity contracts falls short of high market potential. • For this study a consumer choice simulation for electricity contracts was processed. • Higher visibility and involvement increases demand for green electricity contracts. • Branding that enables identity signaling contributes to green energy policy goals

  10. Modelling electricity demand in Ghana revisited: The role of policy regime changes

    International Nuclear Information System (INIS)

    Adom, Philip Kofi; Bekoe, William

    2013-01-01

    As policy regime changes, demand elasticities are unlikely to be constant since individuals change how they form their expectations, and this will change the estimated decision rules. In this paper, the time-varying nature of electricity demand elasticities prior to and post the economic reform period in Ghana is analysed using the FM-OLS. Three different sample periods -pre-reform, post-reform, and full-period- was used in the analysis. The result from the full-sample period revealed that in the long-run electricity demand is significantly affected by industry efficiency, industry value added, and real per capita GDP. Urbanization rate, however, has no significant effect. The pre-reform estimate showed lower income, output, and urbanization elasticities but higher industry energy efficiency elasticity relative to the post-reform period. This suggests that technological change in the pre-reform period has been energy saving whilst technological change in the post reform period has been energy consuming. The result further showed evidence of changing structure of the economy from the more energy intensive sector to the less energy intensive sector after the reform. Government should renew her effort in promoting energy saving technologies in the industrial sector and adjust the industrial structure to encourage the expansion of low energy intensive industries or high technology efficient industries. - Highlights: • The study investigates time-varying nature of demand elasticities prior to 1983 and after 1983. • Result shows differences in demand elasticities prior to and post the reform. • Pre-reform period is characterised with energy saving technology. • Post-reform period is characterised with energy consuming technology. • The post-reform result reveals evidence of gradual structural shift in the economy

  11. Risk management and participation planning of electric vehicles in smart grids for demand response

    International Nuclear Information System (INIS)

    Nezamoddini, Nasim; Wang, Yong

    2016-01-01

    Demand response (DR) can serve as an effective tool to better balance the electricity demand and supply in the smart grid. It is defined as 'the changes in electricity usage by end-use customers from their normal consumption patterns' in response to pricing and incentive payments. This paper focuses on new opportunities for DR with electric vehicles (EVs). EVs are potential distributed energy resources that support both the grid-to-vehicle and vehicle-to-grid modes. Their participation in the time-based (e.g., time-of-use) and incentive-based (e.g., regulation services) DR programs helps improve the stability and reduce the potential risks to the grid. Smart scheduling of EV charging and discharging activities also supports high penetration of renewables with volatile energy generation. This paper proposes a novel stochastic model from the Independent System Operator's perspective for risk management and participation planning of EVs in the smart grid for DR. The risk factors considered in this paper involve those caused by uncertainties in renewables (wind and solar), load patterns, parking patterns, and transmission lines' reliability. The effectiveness of the model in response to various settings such as the area type (residential, commercial, and industrial), the EV penetration level, and the risk level has been investigated. - Highlights: • We identify new opportunities for demand response (DR) using electric vehicles (EVs). • We integrate EVs in both grid-to-vehicle and vehicle-to-grid modes in smart grids. • EV participation for both time- and incentive-based DR programs are modelled. • We consider uncertainties in renewables, load, parking, and transmission lines. • Model case studies are demonstrated in residential, commercial, and industrial areas.

  12. Impact of oil prices, economic diversification policies and energy conservation programs on the electricity and water demands in Kuwait

    International Nuclear Information System (INIS)

    Wood, Michael; Alsayegh, Osamah A.

    2014-01-01

    This paper describes the influences of oil revenue and government's policies toward economic developments and energy efficiency on the electricity and water demands. A Kuwait-specific electricity and water demand model was developed based on historic data of oil income, gross domestic product (GDP), population and electric load and water demand over the past twelve years (1998–2010). Moreover, the model took into account the future mega projects, annual new connected loads and expected application of energy conservation programs. It was run under six circumstances representing the combinations of three oil income scenarios and two government action policies toward economic diversification and energy conservation. The first government policy is the status quo with respect to economic diversification and applying energy conservation programs. The second policy scenario is the proactive strategy of raising the production of the non-oil sector revenue and enforcing legislations toward energy demand side management and conservation. In the upcoming 20 years, the average rates of change of the electric load and water demand increase are 0.13 GW and 3.0 MIGD, respectively, per US dollar oil price increase. Moreover, through proactive policy, the rates of average load and water demand decrease are 0.13 GW and 2.9 MIGD per year, respectively. - Highlights: • Kuwait-specific electricity and water demand model is presented. • Strong association between oil income and electricity and water demands. • Rate of change of electric load per US dollar oil price change is 0.13 GW. • Rate of change of water demand per US dollar oil price change is 3.0 MIGD. • By 2030, efficiency lowers electric load and water demand by 10 and 6%, respectively

  13. Modeling of the Maximum Entropy Problem as an Optimal Control Problem and its Application to Pdf Estimation of Electricity Price

    Directory of Open Access Journals (Sweden)

    M. E. Haji Abadi

    2013-09-01

    Full Text Available In this paper, the continuous optimal control theory is used to model and solve the maximum entropy problem for a continuous random variable. The maximum entropy principle provides a method to obtain least-biased probability density function (Pdf estimation. In this paper, to find a closed form solution for the maximum entropy problem with any number of moment constraints, the entropy is considered as a functional measure and the moment constraints are considered as the state equations. Therefore, the Pdf estimation problem can be reformulated as the optimal control problem. Finally, the proposed method is applied to estimate the Pdf of the hourly electricity prices of New England and Ontario electricity markets. Obtained results show the efficiency of the proposed method.

  14. Evolution and current status of demand response (DR) in electricity markets: Insights from PJM and NYISO

    International Nuclear Information System (INIS)

    Walawalkar, Rahul; Fernands, Stephen; Thakur, Netra; Chevva, Konda Reddy

    2010-01-01

    In electricity markets, traditional demand side management programs are slowly getting replaced with demand response (DR) programs. These programs have evolved since the early pilot programs launched in late 1990s. With the changes in market rules the opportunities have generally increased for DR for participating in emergency, economic and ancillary service programs. In recent times, various regulators have suggested that DR can also be used as a solution to meet supply - demand fluctuations in scenarios with significant penetration of variable renewable sources in grid. This paper provides an overview of the evolution of the DR programs in PJM and NYISO markets as well as analyzes current opportunities. Although DR participation has grown, most of the current participation is in the reliability programs, which are designed to provide load curtailment during peak days. This suggests that there is a significant gap between perception of ability of DR to mitigate variability of renewables and reality of current participation. DR in future can be scaled to play a more dynamic role in electricity markets, but that would require changes both on technology as well as policy front. Advances in building technologies and energy storage combined with appropriate price signals can lead to enhanced DR participation. (author)

  15. Ice Storage Air-Conditioning System Simulation with Dynamic Electricity Pricing: A Demand Response Study

    Directory of Open Access Journals (Sweden)

    Chi-Chun Lo

    2016-02-01

    Full Text Available This paper presents an optimal dispatch model of an ice storage air-conditioning system for participants to quickly and accurately perform energy saving and demand response, and to avoid the over contact with electricity price peak. The schedule planning for an ice storage air-conditioning system of demand response is mainly to transfer energy consumption from the peak load to the partial-peak or off-peak load. Least Squares Regression (LSR is used to obtain the polynomial function for the cooling capacity and the cost of power consumption with a real ice storage air-conditioning system. Based on the dynamic electricity pricing, the requirements of cooling loads, and all technical constraints, the dispatch model of the ice-storage air-conditioning system is formulated to minimize the operation cost. The Improved Ripple Bee Swarm Optimization (IRBSO algorithm is proposed to solve the dispatch model of the ice storage air-conditioning system in a daily schedule on summer. Simulation results indicate that reasonable solutions provide a practical and flexible framework allowing the demand response of ice storage air-conditioning systems to demonstrate the optimization of its energy savings and operational efficiency and offering greater energy efficiency.

  16. Determinants of Electricity Demand in Nonmetallic Mineral Products Industry: Evidence from a Comparative Study of Japan and China

    Directory of Open Access Journals (Sweden)

    Gang Du

    2015-06-01

    Full Text Available Electricity intensity is an important indicator for measuring production efficiency. A comparative study could offer a new perspective on investigating determinants of electricity demand. The Japanese non-metallic mineral products industry is chosen as the object for comparison considering its representative position in production efficiency. By adopting the cointegration model, this paper examines influencing factors of electricity demand in Japanese and Chinese non-metallic mineral products industries under the same framework. Results indicate that although economic growth and industrial development stages are different between the two countries, major factors that affect the sectoral energy consumption are the same. Specifically, economic growth and industrial activity contribute to the growth of sectoral electricity consumption, while R&D intensity, per capita productivity and electricity price are contributors to the decline of sectoral electricity consumption. Finally, in order to further investigate the development trend of sectoral electricity demand, future electricity consumption and conservation potential are predicted under different scenarios. Electricity demand of the Chinese non-metallic mineral products industry is predicted to be 680.53 TWh (terawatt-hours in 2020 and the sectoral electricity conservation potentials are estimated to be 118.26 TWh and 216.25 TWh under the moderate and advanced electricity-saving scenarios, respectively.

  17. Massive coordination of residential embedded electricity generation and demand response using the PowerMatcher approach

    International Nuclear Information System (INIS)

    Kamphuis, I.G.; Hommelberg, M.P.F.; Warmer, C.J.; Kok, J.K.

    2007-01-01

    Different driving forces push the electricity production towards decentralization. The projected increase of distributed power generation on the residential level with an increasing proportion of intermittent renewable energy resources poses problems for continuously matching the energy balance when coordination takes place centrally. On the other hand, new opportunities arise by intelligent clustering of generators and demand in so-called Virtual Power Plants. Part of the responsibility for new coordination mechanisms, then, has to be laid locally. To achieve this, the current electricity infrastructure is expected to evolve into a network of networks (including ICT (Information and Communication Technology)-networks), in which all system parts communicate with one another, are aware of each other's context and may influence each other. In this paper, a multi-agent systems approach, using price signal-vectors from an electronic market is presented as an appropriate technology needed for massive control and coordination tasks in these future electricity networks. The PowerMatcher, a market-based control concept for supply and demand matching (SDM) in electricity networks, is discussed. The results within a simulation study show the ability to raise the simultaneousness of electricity production and consumption within (local) control clusters with cogeneration and heat-pumps by exchanging price signals and coordinated allocation using market algorithms. The control concept, however, can also be applied in other business cases like reduction of imbalance cost in commercial portfolios or virtual power plant operators, utilizing distributed generators. Furthermore, a PowerMatcher-based field test configuration with 15 Stirling-engine powered micro-CHP's is described, which is currently in operation within a field test in the Netherlands

  18. Forecast analysis of the electricity supply-demand balance in France during the summer of 2008. Supply-demand balance analysis during the summer of 2008

    International Nuclear Information System (INIS)

    2008-05-01

    Twice a year, RTE publishes a forecast study of the electricity supply and demand in continental France for the summer and winter periods. The study is based on the information supplied by electric utilities concerning the expected availability of power generation means and on statistical meteorological models. Safety margins are calculated using thousands of probabilistic scenarios combining various production and consumption situations. This report is the forecast study for the summer of 2008

  19. Generation adequacy report on the electricity supply-demand balance in France. 2016 edition + executive summary

    International Nuclear Information System (INIS)

    2016-01-01

    After a presentation of the elaboration framework of this generation adequacy report, and of the objectives of the risk analysis, this report proposes a detailed analysis of electricity consumption in France. It describes the main determining factors of electric power consumption: energy efficiency, economic growth, demography, and transfers and new uses of electricity. It proposes a sector-based analysis of energy demand (housing sector, office building sector, industrial sector, transport, energy and agriculture sectors), and an assessment of perspectives for power consumption. It also proposes a power-based analysis of electricity consumption: influence of temperature on electricity consumption, analysis of the load curve, perspectives for electricity consumption peak. The next part addresses the evolution of electricity supply in France. It presents the existing production fleet, proposes an overview of renewable energies (ground-based wind energy, offshore wind energy and marine energies, solar photovoltaic energy, bio-energies, hydraulic energy), presents some characteristics of the French nuclear fleet (installed capacity, availability), analyses the flame-based thermal fleet (oil-based, coal-based, gas-based combined, combustion turbine, and decentralised thermal installations). It also discusses the issue of load management, and proposes a synthetic overview of the electricity production fleet (supply evolutions on the medium term, evolutions with respect to the 2015 provisional assessment). The next chapter reports a risk analysis on the medium term by presenting indicators of supply safety, by proposing a failure risk analysis (diagnosis on the medium term, comparison with the previous provisional assessment, sensitivity to extreme events), by presenting energy assessments, by reporting sensitivity analysis (to consumption hypotheses, to hypotheses related to the development of renewable energies, to hypotheses related to the nuclear fleet), by reporting

  20. A high-resolution stochastic model of domestic activity patterns and electricity demand

    International Nuclear Information System (INIS)

    Widen, Joakim; Waeckelgard, Ewa

    2010-01-01

    Realistic time-resolved data on occupant behaviour, presence and energy use are important inputs to various types of simulations, including performance of small-scale energy systems and buildings' indoor climate, use of lighting and energy demand. This paper presents a modelling framework for stochastic generation of high-resolution series of such data. The model generates both synthetic activity sequences of individual household members, including occupancy states, and domestic electricity demand based on these patterns. The activity-generating model, based on non-homogeneous Markov chains that are tuned to an extensive empirical time-use data set, creates a realistic spread of activities over time, down to a 1-min resolution. A detailed validation against measurements shows that modelled power demand data for individual households as well as aggregate demand for an arbitrary number of households are highly realistic in terms of end-use composition, annual and diurnal variations, diversity between households, short time-scale fluctuations and load coincidence. An important aim with the model development has been to maintain a sound balance between complexity and output quality. Although the model yields a high-quality output, the proposed model structure is uncomplicated in comparison to other available domestic load models.

  1. Machine Learning for Identifying Demand Patterns of Home Energy Management Systems with Dynamic Electricity Pricing

    Directory of Open Access Journals (Sweden)

    Derck Koolen

    2017-11-01

    Full Text Available Energy management plays a crucial role in providing necessary system flexibility to deal with the ongoing integration of volatile and intermittent energy sources. Demand Response (DR programs enhance demand flexibility by communicating energy market price volatility to the end-consumer. In such environments, home energy management systems assist the use of flexible end-appliances, based upon the individual consumer’s personal preferences and beliefs. However, with the latter heterogeneously distributed, not all dynamic pricing schemes are equally adequate for the individual needs of households. We conduct one of the first large scale natural experiments, with multiple dynamic pricing schemes for end consumers, allowing us to analyze different demand behavior in relation with household attributes. We apply a spectral relaxation clustering approach to show distinct groups of households within the two most used dynamic pricing schemes: Time-Of-Use and Real-Time Pricing. The results indicate that a more effective design of smart home energy management systems can lead to a better fit between customer and electricity tariff in order to reduce costs, enhance predictability and stability of load and allow for more optimal use of demand flexibility by such systems.

  2. Controlling market power and price spikes in electricity networks: Demand-side bidding.

    Science.gov (United States)

    Rassenti, Stephen J; Smith, Vernon L; Wilson, Bart J

    2003-03-04

    In this article we report an experiment that examines how demand-side bidding can discipline generators in a market for electric power. First we develop a treatment without demand-side bidding; two large firms are allocated baseload and intermediate cost generators such that either firm might unilaterally withhold the capacity of its intermediate cost generators from the market to benefit from the supracompetitive prices that would result from only selling its baseload units. In a converse treatment, ownership of some of the intermediate cost generators is transferred from each of these firms to two other firms such that no one firm could unilaterally restrict output to spawn supracompetitive prices. Having established a well controlled data set with price spikes paralleling those observed in the naturally occurring economy, we also extend the design to include demand-side bidding. We find that demand-side bidding completely neutralizes the exercise of market power and eliminates price spikes even in the presence of structural market power.

  3. Entity’s Irregular Demand Scheduling of the Wholesale Electricity Market based on the Forecast of Hourly Price Ratios

    Directory of Open Access Journals (Sweden)

    O. V. Russkov

    2015-01-01

    Full Text Available The article considers a hot issue to forecast electric power demand amounts and prices for the entities of wholesale electricity market (WEM, which are in capacity of a large user with production technology requirements prevailing over hourly energy planning ones. An electric power demand of such entities is on irregular schedule. The article analyses mathematical models, currently applied to forecast demand amounts and prices. It describes limits of time-series models and fundamental ones in case of hourly forecasting an irregular demand schedule of the electricity market entity. The features of electricity trading at WEM are carefully analysed. Factors that influence on irregularity of demand schedule of the metallurgical plant are shown. The article proposes method for the qualitative forecast of market price ratios as a tool to reduce a dependence on the accuracy of forecasting an irregular schedule of demand. It describes the differences between the offered method and the similar ones considered in research studies and scholarly works. The correlation between price ratios and relaxation in the requirements for the forecast accuracy of the electric power consumption is analysed. The efficiency function of forecast method is derived. The article puts an increased focus on description of the mathematical model based on the method of qualitative forecast. It shows main model parameters and restrictions the electricity market imposes on them. The model prototype is described as a programme module. Methods to assess an effectiveness of the proposed forecast model are examined. The positive test results of the model using JSC «Volzhsky Pipe Plant» data are given. A conclusion is drawn concerning the possibility to decrease dependence on the forecast accuracy of irregular schedule of entity’s demand at WEM. The effective trading tool has been found for the entities of irregular demand schedule at WEM. The tool application allows minimizing cost

  4. Forward-looking report of the electricity supply-demand balance in France. 2011

    International Nuclear Information System (INIS)

    2011-01-01

    After an introduction presenting the objective of this report and the method used for its predictions, this document proposes an analysis of energy consumption: past trends, context of predictions, building up of predictions, global predictions, impact of demand control, comparison with a previous forward-looking assessment, comparison with other scenarios and other European countries. It analyses and discusses power consumption predictions (electricity consumption time variations, load curve evolution perspectives, peak power), production supply (current stock, thermal nuclear, thermal fossil, thermal decentralized, hydroelectric, wind energy, and photovoltaic production), the evolution of the supply-demand balance on a medium term for France and for two French regions. It finally proposes a long term prospective vision regarding energy

  5. The forecast of primary energy demand and electricity demand and the participation of coal in covering this demand; Prognoza zapotrzebowania na energie pierwotna i elektryczna oraz udziat wegla w pokryciu tego zapotrzebowania

    Energy Technology Data Exchange (ETDEWEB)

    Solinski, J.

    2004-07-01

    The paper presents a preliminary forecast of Poland's future coal demand until 2030, particularly the demand for electric power. Two scenarios are examined - one of average GDP growth rate of 3.5% and a second of 4.5%. Implementation of the first scenario would enable Poland to achieve in 2030 today's levels of per capita electricity consumption in main EU countries, with a forecast consumption level of 280 TWh. By 2030, coal's share in electricity production would fall to about 7%, the remainder being from gas, nuclear and renewable sources. 11 refs., 5 tabs.

  6. Generation adequacy report on the electricity supply-demand balance in France. 2015 edition + executive summary

    International Nuclear Information System (INIS)

    2016-01-01

    France's new energy transition law for green growth takes effect in 2015, and it will support RTE in its task of assessing and analysing security of electricity supply. Indeed, RTE is required by law to periodically publish Generation Adequacy Reports on the balance between electricity supply and demand. This year's report will be used in security of supply analyses conducted as part of the planning of the next multi-annual energy program. Another highlight of 2015 is the operational implementation of the capacity mechanism. Electricity suppliers now have to contribute to security of supply in proportion to their customers' consumption via a new obligation-based system. The 2015 Generation Adequacy Report was prepared within this context. The supply-demand balance outlook is considerably better over the entire medium-term horizon than in the 2014 Generation Adequacy Report. This is a result of generators' recent decisions to keep oil-fired and combined-cycle gas plants in the market. Included in the possible courses of action RTE identified in its previous Generation Adequacy Report, these decisions were taken just as the capacity mechanism was being implemented operationally. A downward revision of demand assumptions has also improved the security of supply outlook. The 2015 Generation Adequacy Report paints a much more favourable picture of the supply-demand balance over the next five years than the previous edition. Significant margins are foreseen during the next two winters. This year's Generation Adequacy Report also includes detailed assumptions about the evolution of the European mix, which will play an increasingly important role in guaranteeing security of supply in France. Indeed, interconnections will help reduce the shortfall risk by 8 to 10 GW over the next five winters. Lastly, a new chapter about flexibility requirements and the variability of residual demand associated with the growing share of renewable generation in the

  7. Compact stars with a small electric charge: the limiting radius to mass relation and the maximum mass for incompressible matter

    Energy Technology Data Exchange (ETDEWEB)

    Lemos, Jose P.S.; Lopes, Francisco J.; Quinta, Goncalo [Universidade de Lisboa, UL, Departamento de Fisica, Centro Multidisciplinar de Astrofisica, CENTRA, Instituto Superior Tecnico, IST, Lisbon (Portugal); Zanchin, Vilson T. [Universidade Federal do ABC, Centro de Ciencias Naturais e Humanas, Santo Andre, SP (Brazil)

    2015-02-01

    One of the stiffest equations of state for matter in a compact star is constant energy density and this generates the interior Schwarzschild radius to mass relation and the Misner maximum mass for relativistic compact stars. If dark matter populates the interior of stars, and this matter is supersymmetric or of some other type, some of it possessing a tiny electric charge, there is the possibility that highly compact stars can trap a small but non-negligible electric charge. In this case the radius to mass relation for such compact stars should get modifications. We use an analytical scheme to investigate the limiting radius to mass relation and the maximum mass of relativistic stars made of an incompressible fluid with a small electric charge. The investigation is carried out by using the hydrostatic equilibrium equation, i.e., the Tolman-Oppenheimer-Volkoff (TOV) equation, together with the other equations of structure, with the further hypothesis that the charge distribution is proportional to the energy density. The approach relies on Volkoff and Misner's method to solve the TOV equation. For zero charge one gets the interior Schwarzschild limit, and supposing incompressible boson or fermion matter with constituents with masses of the order of the neutron mass one finds that the maximum mass is the Misner mass. For a small electric charge, our analytical approximating scheme, valid in first order in the star's electric charge, shows that the maximum mass increases relatively to the uncharged case, whereas the minimum possible radius decreases, an expected effect since the new field is repulsive, aiding the pressure to sustain the star against gravitational collapse. (orig.)

  8. Modeling Demand Response in Electricity Retail Markets as a Stackelberg Game

    DEFF Research Database (Denmark)

    Zugno, Marco; Morales González, Juan Miguel; Pinson, Pierre

    We model the retail market with dynamic pricing as a Stackelberg game where both retailers (leaders) and flexible consumers (followers) solve an economic cost-minimization problem. The electricity retailer optimizes an economic objective over a daily horizon by setting an hourly price-sequence, w......We model the retail market with dynamic pricing as a Stackelberg game where both retailers (leaders) and flexible consumers (followers) solve an economic cost-minimization problem. The electricity retailer optimizes an economic objective over a daily horizon by setting an hourly price...... with Equilibrium Constraints (MPEC) and cast as a Mixed Integer Linear Program (MILP), which can be solved using off-the-shelf optimization software. In an illustrative example, we consider a retailer associated with both flexible demand and wind power production. Such an example shows the efficiency of dynamic...

  9. Natural graphite demand and supply - Implications for electric vehicle battery requirements

    Science.gov (United States)

    Olson, Donald W.; Virta, Robert L.; Mahdavi, Mahbood; Sangine, Elizabeth S.; Fortier, Steven M.

    2016-01-01

    Electric vehicles have been promoted to reduce greenhouse gas emissions and lessen U.S. dependence on petroleum for transportation. Growth in U.S. sales of electric vehicles has been hindered by technical difficulties and the high cost of the lithium-ion batteries used to power many electric vehicles (more than 50% of the vehicle cost). Groundbreaking has begun for a lithium-ion battery factory in Nevada that, at capacity, could manufacture enough batteries to power 500,000 electric vehicles of various types and provide economies of scale to reduce the cost of batteries. Currently, primary synthetic graphite derived from petroleum coke is used in the anode of most lithium-ion batteries. An alternate may be the use of natural flake graphite, which would result in estimated graphite cost reductions of more than US$400 per vehicle at 2013 prices. Most natural flake graphite is sourced from China, the world's leading graphite producer. Sourcing natural flake graphite from deposits in North America could reduce raw material transportation costs and, given China's growing internal demand for flake graphite for its industries and ongoing environmental, labor, and mining issues, may ensure a more reliable and environmentally conscious supply of graphite. North America has flake graphite resources, and Canada is currently a producer, but most new mining projects in the United States require more than 10 yr to reach production, and demand could exceed supplies of flake graphite. Natural flake graphite may serve only to supplement synthetic graphite, at least for the short-term outlook.

  10. Research on industrialization of electric vehicles with its demand forecast using exponential smoothing method

    Directory of Open Access Journals (Sweden)

    Zhanglin Peng

    2015-04-01

    Full Text Available Purpose: Electric vehicles industry has gotten a rapid development in the world, especially in the developed countries, but still has a gap among different countries or regions. The advanced industrialization experiences of the EVs in the developed countries will have a great helpful for the development of EVs industrialization in the developing countries. This paper seeks to research the industrialization path & prospect of American EVs by forecasting electric vehicles demand and its proportion to the whole car sales based on the historical 37 EVs monthly sales and Cars monthly sales spanning from Dec. 2010 to Dec. 2013, and find out the key measurements to help Chinese government and automobile enterprises to promote Chinese EVs industrialization. Design/methodology: Compared with Single Exponential Smoothing method and Double Exponential Smoothing method, Triple exponential smoothing method is improved and applied in this study. Findings: The research results show that:  American EVs industry will keep a sustained growth in the next 3 months.  Price of the EVs, price of fossil oil, number of charging station, EVs technology and the government market & taxation polices have a different influence to EVs sales. So EVs manufacturers and policy-makers can adjust or reformulate some technology tactics and market measurements according to the forecast results. China can learn from American EVs polices and measurements to develop Chinese EVs industry. Originality/value: The main contribution of this paper is to use the triple exponential smoothing method to forecast the electric vehicles demand and its proportion to the whole automobile sales, and analyze the industrial development of Chinese electric vehicles by American EVs industry.

  11. Forecasting Monthly Electricity Demands by Wavelet Neuro-Fuzzy System Optimized by Heuristic Algorithms

    Directory of Open Access Journals (Sweden)

    Jeng-Fung Chen

    2018-02-01

    Full Text Available Electricity load forecasting plays a paramount role in capacity planning, scheduling, and the operation of power systems. Reliable and accurate planning and prediction of electricity load are therefore vital. In this study, a novel approach for forecasting monthly electricity demands by wavelet transform and a neuro-fuzzy system is proposed. Firstly, the most appropriate inputs are selected and a dataset is constructed. Then, Haar wavelet transform is utilized to decompose the load data and eliminate noise. In the model, a hierarchical adaptive neuro-fuzzy inference system (HANFIS is suggested to solve the curse-of-dimensionality problem. Several heuristic algorithms including Gravitational Search Algorithm (GSA, Cuckoo Optimization Algorithm (COA, and Cuckoo Search (CS are utilized to optimize the clustering parameters which help form the rule base, and adaptive neuro-fuzzy inference system (ANFIS optimize the parameters in the antecedent and consequent parts of each sub-model. The proposed approach was applied to forecast the electricity load of Hanoi, Vietnam. The constructed models have shown high forecasting performances based on the performance indices calculated. The results demonstrate the validity of the approach. The obtained results were also compared with those of several other well-known methods including autoregressive integrated moving average (ARIMA and multiple linear regression (MLR. In our study, the wavelet CS-HANFIS model outperformed the others and provided more accurate forecasting.

  12. Application of residual modification approach in seasonal ARIMA for electricity demand forecasting: A case study of China

    International Nuclear Information System (INIS)

    Wang Yuanyuan; Wang Jianzhou; Zhao Ge; Dong Yao

    2012-01-01

    Electricity demand forecasting could prove to be a useful policy tool for decision-makers; thus, accurate forecasting of electricity demand is valuable in allowing both power generators and consumers to make their plans. Although a seasonal ARIMA model is widely used in electricity demand analysis and is a high-precision approach for seasonal data forecasting, errors are unavoidable in the forecasting process. Consequently, a significant research goal is to further improve forecasting precision. To help people in the electricity sectors make more sensible decisions, this study proposes residual modification models to improve the precision of seasonal ARIMA for electricity demand forecasting. In this study, PSO optimal Fourier method, seasonal ARIMA model and combined models of PSO optimal Fourier method with seasonal ARIMA are applied in the Northwest electricity grid of China to correct the forecasting results of seasonal ARIMA. The modification models forecasting of the electricity demand appears to be more workable than that of the single seasonal ARIMA. The results indicate that the prediction accuracy of the three residual modification models is higher than the single seasonal ARIMA model and that the combined model is the most satisfactory of the three models. - Highlights: ► Three residual modification models are proposed to improve the precision of seasonal ARIMA. ► Accurate electricity demand forecast is helpful for a power production sector to come to a correct and reasonable decision. ► The results conclude that the residual modification approaches could enhance the prediction accuracy of seasonal ARIMA. ► The modification models could be applied to forecast electricity demand.

  13. Electricity Demand Projection Using a Path-Coefficient Analysis and BAG-SA Approach: A Case Study of China

    Directory of Open Access Journals (Sweden)

    Qunli Wu

    2017-01-01

    Full Text Available Path-coefficient analysis is utilized to investigate the direct and indirect effects of economic growth, population growth, urbanization rate, industrialization level, and carbon intensity on electricity demand of China. To improve the projection accuracy of electricity demand, this study proposes a hybrid bat algorithm, Gaussian perturbations, and simulated annealing (BAG-SA optimization method. The proposed BAG-SA algorithm not only inherits the simplicity and efficiency of the standard BA with a capability of searching for global optimality but also enhances local search ability and speeds up the global convergence rate. The BAG-SA algorithm is employed to optimize the coefficients of the multiple linear and quadratic forms of electricity demand estimation model. Results indicate that the proposed algorithm has higher precision and reliability than the coefficients optimized by other single-optimization methods, such as genetic algorithm, particle swarm optimization algorithm, or bat algorithm. And the quadratic form of BAG-SA electricity demand estimation model has better fitting ability compared with the multiple linear form of the model. Therefore, the quadratic form of the model is applied to estimate electricity demand of China from 2016 to 2030. The findings of this study demonstrate that China’s electricity demand will reach 14925200 million KWh in 2030.

  14. Integrating Demand-Side Resources into the Electric Grid: Economic and Environmental Considerations

    Science.gov (United States)

    Fisher, Michael J.

    Demand-side resources are taking an increasingly prominent role in providing essential grid services once provided by thermal power plants. This thesis considers the economic feasibility and environmental effects of integrating demand-side resources into the electric grid with consideration given to the diversity of market and environmental conditions that can affect their behavior. Chapter 2 explores the private economics and system-level carbon dioxide reduction when using demand response for spinning reserve. Steady end uses like lighting are more than twice as profitable as seasonal end uses because spinning reserve is needed year-round. Avoided carbon emission damages from using demand response instead of fossil fuel generation for spinning reserve are sufficient to justify incentives for demand response resources. Chapter 3 quantifies the system-level net emissions rate and private economics of behind-the-meter energy storage. Net emission rates are lower than marginal emission rates for power plants and in-line with estimates of net emission rates from grid-level storage. The economics are favorable for many buildings in regions with high demand charges like California and New York, even without subsidies. Future penetration into regions with average charges like Pennsylvania will depend greatly on installation cost reductions and wholesale prices for ancillary services. Chapter 4 outlines a novel econometric model to quantify potential revenues from energy storage that reduces demand charges. The model is based on a novel predictive metric that is derived from the building's load profile. Normalized revenue estimates are independent of the power capacity of the battery holding other performance characteristics equal, which can be used to calculate the profit-maximizing storage size. Chapter 5 analyzes the economic feasibility of flow batteries in the commercial and industrial market. Flow batteries at a 4-hour duration must be less expensive on a dollar per

  15. Determining optimal interconnection capacity on the basis of hourly demand and supply functions of electricity

    International Nuclear Information System (INIS)

    Keppler, Jan Horst; Meunier, William; Coquentin, Alexandre

    2017-01-01

    Interconnections for cross-border electricity flows are at the heart of the project to create a common European electricity market. At the time, increase in production from variable renewables clustered during a limited numbers of hours reduces the availability of existing transport infrastructures. This calls for higher levels of optimal interconnection capacity than in the past. In complement to existing scenario-building exercises such as the TYNDP that respond to the challenge of determining optimal levels of infrastructure provision, the present paper proposes a new empirically-based methodology to perform Cost-Benefit analysis for the determination of optimal interconnection capacity, using as an example the French-German cross-border trade. Using a very fine dataset of hourly supply and demand curves (aggregated auction curves) for the year 2014 from the EPEX Spot market, it constructs linearized net export (NEC) and net import demand curves (NIDC) for both countries. This allows assessing hour by hour the welfare impacts for incremental increases in interconnection capacity. Summing these welfare increases over the 8 760 hours of the year, this provides the annual total for each step increase of interconnection capacity. Confronting welfare benefits with the annual cost of augmenting interconnection capacity indicated the socially optimal increase in interconnection capacity between France and Germany on the basis of empirical market micro-data. (authors)

  16. Hierarchical Load Tracking Control of a Grid-connected Solid Oxide Fuel Cell for Maximum Electrical Efficiency Operation

    DEFF Research Database (Denmark)

    Li, Yonghui; Wu, Qiuwei; Zhu, Haiyu

    2015-01-01

    efficiency operation obtained at different active power output levels, a hierarchical load tracking control scheme for the grid-connected SOFC was proposed to realize the maximum electrical efficiency operation with the stack temperature bounded. The hierarchical control scheme consists of a fast active...... power control and a slower stack temperature control. The active power control was developed by using a decentralized control method. The efficiency of the proposed hierarchical control scheme was demonstrated by case studies using the benchmark SOFC dynamic model......Based on the benchmark solid oxide fuel cell (SOFC) dynamic model for power system studies and the analysis of the SOFC operating conditions, the nonlinear programming (NLP) optimization method was used to determine the maximum electrical efficiency of the grid-connected SOFC subject...

  17. Sensitivity of district heating system operation to heat demand reductions and electricity price variations: A Swedish example

    International Nuclear Information System (INIS)

    Åberg, M.; Widén, J.; Henning, D.

    2012-01-01

    In the future, district heating companies in Sweden must adapt to energy efficiency measures in buildings and variable fuel and electricity prices. Swedish district heating demands are expected to decrease by 1–2% per year and electricity price variations seem to be more unpredictable in the future. A cost-optimisation model of a Swedish local district heating system is constructed using the optimisation modelling tool MODEST. A scenario for heat demand changes due to increased energy efficiency in buildings, combined with the addition of new buildings, is studied along with a sensitivity analysis for electricity price variations. Despite fears that heat demand reductions will decrease co-generation of clean electricity and cause increased global emissions, the results show that anticipated heat demand changes do not increase the studied system's primary energy use or global CO 2 emissions. The results further indicate that the heat production plants and the fuels used within the system have crucial importance for the environmental impact of district heat use. Results also show that low seasonal variations in electricity price levels with relatively low winter prices promote the use of electric heat pumps. High winter prices on the other hand promote co-generation of heat and electricity in CHP plants. -- Highlights: ► A MODEST optimisation model of the Uppsala district heating system is built. ► The impact of heat demand change on heat and electricity production is examined. ► An electricity price level sensitivity analysis for district heating is performed. ► Heat demand changes do not increase the primary energy use or global CO 2 emissions. ► Low winter prices promote use of electric heat pumps for district heating production.

  18. A review of the costs and benefits of demand response for electricity in the UK

    International Nuclear Information System (INIS)

    Bradley, Peter; Leach, Matthew; Torriti, Jacopo

    2013-01-01

    The recent policy discussion in the UK on the economic case for demand response (DR) calls for a reflection on available evidence regarding its costs and benefits. Existing studies tend to consider the size of investments and returns of certain forms of DR in isolation and do not consider economic welfare effects. From review of existing studies, policy documents, and some simple modelling of benefits of DR in providing reserve for unforeseen events, we demonstrate that the economic case for DR in UK electricity markets is positive. Consideration of economic welfare gains is provided. - Highlights: ► The paper clearly articulates the range of benefits and costs from demand response. ► Estimates for benefits and costs are converted into a broadly comparable basis. ► It is found that a positive case exists for demand response in the UK. ► New quantitative modelling is provided for one UK benefit not found in the literature. ► Economic welfare gain is considered in assessment; other UK papers do not consider such effects.

  19. Regional electric power demand elasticities of Japan's industrial and commercial sectors

    International Nuclear Information System (INIS)

    Hosoe, Nobuhiro; Akiyama, Shu-ichi

    2009-01-01

    In the assessment and review of regulatory reforms in the electric power market, price elasticity is one of the most important parameters that characterize the market. However, price elasticity has seldom been estimated in Japan; instead, it has been assumed to be as small as 0.1 or 0 without proper examination of the empirical validity of such a priori assumptions. We estimated the regional power demand functions for nine regions, in order to quantify the elasticity, and found the short-run price elasticity to be 0.09-0.30 and the long-run price elasticity to be 0.12-0.56. Inter-regional comparison of our estimation results suggests that price elasticity in rural regions is larger than that in urban regions. Popular assumptions of small elasticity of 0.1, for example, could be suitable for examining Japan's aggregate power demand but not power demand functions that focus on respective regions. Furthermore, assumptions about smaller elasticity values such as 0.01 and 0 could not be supported statistically by this study.

  20. Regional electric power demand elasticities of Japan's industrial and commercial sectors

    Energy Technology Data Exchange (ETDEWEB)

    Hosoe, Nobuhiro [National Graduate Institute for Policy Studies, 7-22-1 Roppongi, Minato, Tokyo 106-8677 (Japan); Akiyama, Shu-ichi [Kushiro Public University of Economics, 4-1-1 Ashino, Kushiro, Hokkaido 085-8585 (Japan)

    2009-11-15

    In the assessment and review of regulatory reforms in the electric power market, price elasticity is one of the most important parameters that characterize the market. However, price elasticity has seldom been estimated in Japan; instead, it has been assumed to be as small as 0.1 or 0 without proper examination of the empirical validity of such a priori assumptions. We estimated the regional power demand functions for nine regions, in order to quantify the elasticity, and found the short-run price elasticity to be 0.09-0.30 and the long-run price elasticity to be 0.12-0.56. Inter-regional comparison of our estimation results suggests that price elasticity in rural regions is larger than that in urban regions. Popular assumptions of small elasticity of 0.1, for example, could be suitable for examining Japan's aggregate power demand but not power demand functions that focus on respective regions. Furthermore, assumptions about smaller elasticity values such as 0.01 and 0 could not be supported statistically by this study. (author)

  1. An analysis of the factors influencing demand-side management activity in the electric utility industry

    Science.gov (United States)

    Bock, Mark Joseph

    Demand-side management (DSM), defined as the "planning, implementation, and monitoring of utility activities designed to encourage consumers to modify their pattern of electricity usage, including the timing and level of electricity demand," is a relatively new concept in the U.S. electric power industry. Nevertheless, in twenty years since it was first introduced, utility expenditures on DSM programs, as well as the number of such programs, have grown rapidly. At first glance, it may seem peculiar that a firm would actively attempt to reduce demand for its primary product. There are two primary explanations as to why a utility might pursue DSM: regulatory mandate, and self-interest. The purpose of this dissertation is to determine the impact these influences have on the amount of DSM undertaken by utilities. This research is important for two reasons. First, it provides insight into whether DSM will continue to exist as competition becomes more prevalent in the industry. Secondly, it is important because no one has taken a comprehensive look at firm-level DSM activity on an industry-wide basis. The primary data set used in this dissertation is the U.S. Department of Energy's Annual Electric Utility Report, Form EIA-861, which represents the most comprehensive data set available for analyzing DSM activity in the U.S. There are four measures of DSM activity in this data set: (1) utility expenditures on DSM programs; (2) energy savings by DSM program participants; and (3) the actual and (4) the potential reductions in peak load resulting from utility DSM measures. Each is used as the dependent variable in an econometric analysis where independent variables include various utility characteristics, regulatory characteristics, and service territory and customer characteristics. In general, the results from the econometric analysis suggest that in 1993, DSM activity was primarily the result of regulatory pressure. All of the evidence suggests that if DSM continues to

  2. Stopping coal-fired electricity imports on smog days : a review of the OPA's proposed 250 MW demand response program

    International Nuclear Information System (INIS)

    Gibbons, J.

    2006-01-01

    This paper proposed an alternative to importing coal-fired electricity from the Ohio Valley on smog alert days in Ontario. It was suggested that the Ontario Power Authority (OPA) should pay large electricity consumers to shift some of their consumption from peak to off-peak hours. It was observed that demand response programs which pay consumers to shift demands to off-peak hours can provide multiple benefits to Ontario, including reduced air pollution on smog-alert days, a reduction in the spot price of electricity and reduced price volatility. In addition, demand response programs reduce the risk of blackouts and brownouts, as well as the need for new electricity generation and transmission infrastructure. It was noted that the Independent Electricity System Operator (IESO) and the OPA are planning to introduce demand response programs for the summer of 2006. However, the IESO's emergency load reduction program will be operated only during emergency situations to avoid the need for voltage reductions, while the OPA proposes to introduce a non-emergency demand response program which will be activated during most smog-alert days. Various amendments to the proposed program were suggested in this paper, including the establishment of price parity with coal-fired electricity imports; the provision of notification by 3 PM of the need for demand reductions the following day; no capping on the quantity of demand reductions that the OPA will purchase at a lower cost than electricity imports; and that the OPA's proposed Capacity Building Demand Response Program should proceed as quickly as possible without a pre-determined MW cap. 4 refs., 6 figs

  3. Improved estimation of electricity demand function by integration of fuzzy system and data mining approach

    International Nuclear Information System (INIS)

    Azadeh, A.; Saberi, M.; Ghaderi, S.F.; Gitiforouz, A.; Ebrahimipour, V.

    2008-01-01

    This study presents an integrated fuzzy system, data mining and time series framework to estimate and predict electricity demand for seasonal and monthly changes in electricity consumption especially in developing countries such as China and Iran with non-stationary data. Furthermore, it is difficult to model uncertain behavior of energy consumption with only conventional fuzzy system or time series and the integrated algorithm could be an ideal substitute for such cases. To construct fuzzy systems, a rule base is needed. Because a rule base is not available, for the case of demand function, look up table which is one of the extracting rule methods is used to extract the rule base. This system is defined as FLT. Also, decision tree method which is a data mining approach is similarly utilized to extract the rule base. This system is defined as FDM. Preferred time series model is selected from linear (ARMA) and nonlinear model. For this, after selecting preferred ARMA model, McLeod-Li test is applied to determine nonlinearity condition. When, nonlinearity condition is satisfied, preferred nonlinear model is selected and compare with preferred ARMA model and finally one of this is selected as time series model. At last, ANOVA is used for selecting preferred model from fuzzy models and time series model. Also, the impact of data preprocessing and postprocessing on the fuzzy system performance is considered by the algorithm. In addition, another unique feature of the proposed algorithm is utilization of autocorrelation function (ACF) to define input variables, whereas conventional methods which use trial and error method. Monthly electricity consumption of Iran from 1995 to 2005 is considered as the case of this study. The MAPE estimation of genetic algorithm (GA), artificial neural network (ANN) versus the proposed algorithm shows the appropriateness of the proposed algorithm

  4. Electricity demand loads modeling using AutoRegressive Moving Average (ARMA) models

    Energy Technology Data Exchange (ETDEWEB)

    Pappas, S.S. [Department of Information and Communication Systems Engineering, University of the Aegean, Karlovassi, 83 200 Samos (Greece); Ekonomou, L.; Chatzarakis, G.E. [Department of Electrical Engineering Educators, ASPETE - School of Pedagogical and Technological Education, N. Heraklion, 141 21 Athens (Greece); Karamousantas, D.C. [Technological Educational Institute of Kalamata, Antikalamos, 24100 Kalamata (Greece); Katsikas, S.K. [Department of Technology Education and Digital Systems, University of Piraeus, 150 Androutsou Srt., 18 532 Piraeus (Greece); Liatsis, P. [Division of Electrical Electronic and Information Engineering, School of Engineering and Mathematical Sciences, Information and Biomedical Engineering Centre, City University, Northampton Square, London EC1V 0HB (United Kingdom)

    2008-09-15

    This study addresses the problem of modeling the electricity demand loads in Greece. The provided actual load data is deseasonilized and an AutoRegressive Moving Average (ARMA) model is fitted on the data off-line, using the Akaike Corrected Information Criterion (AICC). The developed model fits the data in a successful manner. Difficulties occur when the provided data includes noise or errors and also when an on-line/adaptive modeling is required. In both cases and under the assumption that the provided data can be represented by an ARMA model, simultaneous order and parameter estimation of ARMA models under the presence of noise are performed. The produced results indicate that the proposed method, which is based on the multi-model partitioning theory, tackles successfully the studied problem. For validation purposes the produced results are compared with three other established order selection criteria, namely AICC, Akaike's Information Criterion (AIC) and Schwarz's Bayesian Information Criterion (BIC). The developed model could be useful in the studies that concern electricity consumption and electricity prices forecasts. (author)

  5. Electric power market liberalization and demand-side management (DSM); Denryoku shijo jiyuka to DSM

    Energy Technology Data Exchange (ETDEWEB)

    Yajima, M. [Central Research Institute of Electric Power Industry, Tokyo (Japan)

    1997-01-30

    This paper explains effects of market liberalization which will lead to introducing competition in electric power business on demand-side management (DSM), by quoting examples mainly in the United States. The paper also describes the future outlook thereon. The DSM program in the United States has expanded for the period between 1989 through 1994. However, during the last few years, the movements of electric power market liberalization have come to force electric power business entities to change their management strategies and reduction in expense. This situation has resulted in reduction in the DSM budget. Future DSM programs are thought to diversify into the following types: a program such as load management which has effect of reducing expenses and investments in investment time periods of 5 to 10 years, a program effective for users such as high-efficiency motors which have effects of reducing expenses and improving efficiency in investment time periods of 3 to 5 years, a program which will be effective enough if market barriers are removed after the market conversions, but requires subsidies and purchase guarantees, and a social program intended for environmental effects and low-income users. 4 refs., 1 tab.

  6. A Complex Network Approach for the Estimation of the Energy Demand of Electric Mobility.

    Science.gov (United States)

    Mureddu, Mario; Facchini, Angelo; Scala, Antonio; Caldarelli, Guido; Damiano, Alfonso

    2018-01-10

    We study how renewable energy impacts regional infrastructures considering the full deployment of electric mobility at that scale. We use the Sardinia Island in Italy as a paradigmatic case study of a semi-closed system both by energy and mobility point of view. Human mobility patterns are estimated by means of census data listing the mobility dynamics of about 700,000 vehicles, the energy demand is estimated by modeling the charging behavior of electric vehicle owners. Here we show that current renewable energy production of Sardinia is able to sustain the commuter mobility even in the theoretical case of a full switch from internal combustion vehicles to electric ones. Centrality measures from network theory on the reconstructed network of commuter trips allows to identify the most important areas (hubs) involved in regional mobility. The analysis of the expected energy flows reveals long-range effects on infrastructures outside metropolitan areas and points out that the most relevant unbalances are caused by spatial segregation between production and consumption areas. Finally, results suggest the adoption of planning actions supporting the installation of renewable energy plants in areas mostly involved by the commuting mobility, avoiding spatial segregation between consumption and generation areas.

  7. Determinants of electricity demand for newly electrified low-income African households

    International Nuclear Information System (INIS)

    Louw, Kate; Conradie, Beatrice; Howells, Mark; Dekenah, Marcus

    2008-01-01

    Access to clean, affordable and appropriate energy is an important enabler of development. Energy allows households to meet their most basic subsistence needs; it is a central feature of all the millennium development goals (MDGs) and, while a lack of access to energy may not be a cause of poverty, addressing the energy needs of the impoverished lets them access services which in turn address the causes of poverty. While much is known about the factors affecting the decisions made when choosing between fuel types within a household, few quantitative studies have been carried out in South Africa to determine the extent to which these factors affect energy choice decisions. It is assumed that the factors traditionally included in economic demand such as price and income of the household affect choice; tastes and preferences as well as external factors such as distance to fuel suppliers are expected to influence preferences. This study follows two typical low-income rural sites in South Africa, Antioch and Garagapola, where the Electricity Basic Services Support Tariff (EBSST) was piloted in 2002. The EBSST is set at 50 kWh/month per household for low domestic consumers; this is worth approximately R20 (±US$3). This subsidy is a lifeline tariff, where households receive the set amount of units per month, free of charge irrespective of whether more units are purchased. These data (collected in 2001 and 2002), recently collated with detailed electricity consumption data, allow us to determine the drivers of electricity consumption within these households. The sample analysed is taken from the initial phase of the study, when no FBE had been introduced to the households. This enabled the study presented here to make use of the well-populated datasets to assess what affects the electricity use decision in these households. This paper attempts to assess which factors affected the decision-making process for electricity consumption within these households. A brief history

  8. Projection of electrical demand in Argentina for the period from 1993 through 2010 mark of economic reform

    International Nuclear Information System (INIS)

    Goni, Margarita R.; Gonzalez, Enrique

    1996-01-01

    A projection of electrical demand for two different scenarios has been presented . The period 1993-2010 is analysed and 1993 has been taken as base year. In this study MAED program was used as well as all available information from INDEC (National Statistical Body), CAMMESA (Electrical Market Company) and Ministry of Economy. The results in the base year achieved an accuracy higher than 98%. The scenarios described different rates of growth and electrical energy uses

  9. The long-term forecast of Pakistan's electricity supply and demand: An application of long range energy alternatives planning

    International Nuclear Information System (INIS)

    Perwez, Usama; Sohail, Ahmed; Hassan, Syed Fahad; Zia, Usman

    2015-01-01

    The long-term forecasting of electricity demand and supply has assumed significant importance in fundamental research to provide sustainable solutions to the electricity issues. In this article, we provide an overview of structure of electric power sector of Pakistan and a summary of historical electricity demand & supply data, current status of divergent set of energy policies as a framework for development and application of a LEAP (Long-range Energy Alternate Planning) model of Pakistan's electric power sector. Pakistan's LEAP model is used to analyze the supply policy selections and demand assumptions for future power generation system on the basis of economics, technicality and implicit environmental implications. Three scenarios are enacted over the study period (2011–2030) which include BAU (Business-As-Usual), NC (New Coal) & GF (Green Future). The results of these scenarios are compared in terms of projected electricity demand & supply, net present cost analysis (discount rate at 4%, 7% and 10%) and GHG (greenhouse gas) emission reductions, along with sensitivity analysis to study the effect of varying parameters on total cost. A concluding section illustrates the policy implications of model for futuristic power generation and environmental policies in Pakistan. - Highlights: • Pakistan-specific electricity demand model is presented. • None of the scenarios exceeded the price of 12 US Cents/kWh. • By 2030, fuel cost is the most dominant factor to influence electricity per unit cost. • By 2030, CO_2 emissions per unit electricity will increase significantly in coal scenario relative to others. • By 2030, the penetration of renewable energy and conservation policies can save 70.6 tWh electricity.

  10. Assessing the influence of manufacturing sectors on electricity demand. A cross-country input-output approach

    Energy Technology Data Exchange (ETDEWEB)

    Tarancon, Miguel Angel; Callejas Albinana, Fernando [Faculty of Law and Social Sciences, Universidad de Castilla - La Mancha, Ronda de Toledo s/n, 13071 Ciudad Real (Spain); Del Rio, Pablo [Institute for Public Policies and Goods (IPP), Centro de Ciencias Humanas y Sociales, CSIC, C/Albasanz 26-28, 28037 Madrid (Spain)

    2010-04-15

    The production and consumption of electricity is a major source of CO{sub 2} emissions in Europe and elsewhere. In turn, the manufacturing sectors are significant end-users of electricity. In contrast to most papers in the literature, which focus on the supply-side, this study tackles the demand-side of electricity. An input-output approach combined with a sensitivity analysis has been developed to analyse the direct and indirect consumptions of electricity by eighteen manufacturing sectors in fifteen European countries, with indirect electricity demand related to the purchase of industrial products from other sectors which, in turn, require the consumption of electricity in their manufacturing processes. We identify the industrial transactions and sectors, which account for a greater share of electricity demand. In addition, the impact of an electricity price increase on the costs and prices of manufacturing products is simulated through a price model, allowing us to identify those sectors whose manufacturing costs are most sensitive to an increase in the electricity price. (author)

  11. Assessing the influence of manufacturing sectors on electricity demand. A cross-country input-output approach

    International Nuclear Information System (INIS)

    Tarancon, Miguel Angel; Callejas Albinana, Fernando; Del Rio, Pablo

    2010-01-01

    The production and consumption of electricity is a major source of CO 2 emissions in Europe and elsewhere. In turn, the manufacturing sectors are significant end-users of electricity. In contrast to most papers in the literature, which focus on the supply-side, this study tackles the demand-side of electricity. An input-output approach combined with a sensitivity analysis has been developed to analyse the direct and indirect consumptions of electricity by eighteen manufacturing sectors in fifteen European countries, with indirect electricity demand related to the purchase of industrial products from other sectors which, in turn, require the consumption of electricity in their manufacturing processes. We identify the industrial transactions and sectors, which account for a greater share of electricity demand. In addition, the impact of an electricity price increase on the costs and prices of manufacturing products is simulated through a price model, allowing us to identify those sectors whose manufacturing costs are most sensitive to an increase in the electricity price. (author)

  12. Density prediction and dimensionality reduction of mid-term electricity demand in China: A new semiparametric-based additive model

    International Nuclear Information System (INIS)

    Shao, Zhen; Yang, Shan-Lin; Gao, Fei

    2014-01-01

    Highlights: • A new stationary time series smoothing-based semiparametric model is established. • A novel semiparametric additive model based on piecewise smooth is proposed. • We model the uncertainty of data distribution for mid-term electricity forecasting. • We provide efficient long horizon simulation and extraction for external variables. • We provide stable and accurate density predictions for mid-term electricity demand. - Abstract: Accurate mid-term electricity demand forecasting is critical for efficient electric planning, budgeting and operating decisions. Mid-term electricity demand forecasting is notoriously complicated, since the demand is subject to a range of external drivers, such as climate change, economic development, which will exhibit monthly, seasonal, and annual complex variations. Conventional models are based on the assumption that original data is stable and normally distributed, which is generally insignificant in explaining actual demand pattern. This paper proposes a new semiparametric additive model that, in addition to considering the uncertainty of the data distribution, includes practical discussions covering the applications of the external variables. To effectively detach the multi-dimensional volatility of mid-term demand, a novel piecewise smooth method which allows reduction of the data dimensionality is developed. Besides, a semi-parametric procedure that makes use of bootstrap algorithm for density forecast and model estimation is presented. Two typical cases in China are presented to verify the effectiveness of the proposed methodology. The results suggest that both meteorological and economic variables play a critical role in mid-term electricity consumption prediction in China, while the extracted economic factor is adequate to reveal the potentially complex relationship between electricity consumption and economic fluctuation. Overall, the proposed model can be easily applied to mid-term demand forecasting, and

  13. Improved proprioceptive function by application of subsensory electrical noise: Effects of aging and task-demand.

    Science.gov (United States)

    Toledo, Diana R; Barela, José A; Kohn, André F

    2017-09-01

    The application of subsensory noise stimulation over the lower limbs has been shown to improve proprioception and postural control under certain conditions. Whereas the effect specificity seems to depend on several factors, studies are still needed to determine the appropriate method for training and rehabilitation purposes. In the current study, we investigated whether the application of subsensory electrical noise over the legs improves proprioceptive function in young and older adults. We aimed to provide evidence that stronger and age-related differential effects occur in more demanding tasks. Proprioceptive function was initially assessed by testing the detection of passive ankle movement (kinesthetic perception) in twenty-eight subjects (14 young and 14 older adults). Thereafter, postural control was assessed during tasks with different sensory challenges: i) by removing visual information (eyes closed) and; ii) by moving the visual scene (moving room paradigm). Tests performed with the application of electrical noise stimulation were compared to those performed without noise. The results showed that electrical noise applied over the legs led to a reduction in the response time to kinesthetic perception in both young and older adults. On the other hand, the magnitude of postural sway was reduced by noise stimulation only during a more challenging task, namely, when the optical flow was changing in an unpredictable (nonperiodic) manner. No differential effects of stimulation between groups were observed. These findings suggest that the relevance of proprioceptive inputs in tasks with different challenges, but not the subjects' age, is a determining factor for sensorimotor improvements due to electrical noise stimulation. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

  14. A fuzzy-stochastic simulation-optimization model for planning electric power systems with considering peak-electricity demand: A case study of Qingdao, China

    International Nuclear Information System (INIS)

    Yu, L.; Li, Y.P.; Huang, G.H.

    2016-01-01

    In this study, a FSSOM (fuzzy-stochastic simulation-optimization model) is developed for planning EPS (electric power systems) with considering peak demand under uncertainty. FSSOM integrates techniques of SVR (support vector regression), Monte Carlo simulation, and FICMP (fractile interval chance-constrained mixed-integer programming). In FSSOM, uncertainties expressed as fuzzy boundary intervals and random variables can be effectively tackled. In addition, SVR coupled Monte Carlo technique is used for predicting the peak-electricity demand. The FSSOM is applied to planning EPS for the City of Qingdao, China. Solutions of electricity generation pattern to satisfy the city's peak demand under different probability levels and p-necessity levels have been generated. Results reveal that the city's electricity supply from renewable energies would be low (only occupying 8.3% of the total electricity generation). Compared with the energy model without considering peak demand, the FSSOM can better guarantee the city's power supply and thus reduce the system failure risk. The findings can help decision makers not only adjust the existing electricity generation/supply pattern but also coordinate the conflict interaction among system cost, energy supply security, pollutant mitigation, as well as constraint-violation risk. - Highlights: • FSSOM (Fuzzy-stochastic simulation-optimization model) is developed for planning EPS. • It can address uncertainties as fuzzy-boundary intervals and random variables. • FSSOM can satisfy peak-electricity demand and optimize power allocation. • Solutions under different probability levels and p-necessity levels are analyzed. • Results create tradeoff among system cost and peak-electricity demand violation risk.

  15. Review of Real-time Electricity Markets for Integrating Distributed Energy Resources and Demand Response

    DEFF Research Database (Denmark)

    Wang, Qi; Zhang, Chunyu; Ding, Yi

    2015-01-01

    The high penetration of both Distributed Energy Resources (DER) and Demand Response (DR) in modern power systems requires a sequence of advanced strategies and technologies for maintaining system reliability and flexibility. Real-time electricity markets (RTM) are the nondiscriminatory transaction...... platforms for providing necessary balancing services, where the market clearing (nodal or zonal prices depending on markets) is very close to real time operations of power systems. One of the primary functions of RTMs in modern power systems is establishing an efficient and effective mechanism for small DER...... and DR to participate in balancing market transactions, while handling their meteorological or intermittent characteristics, facilitating asset utilization, and stimulating their active responses. Consequently, RTMs are dedicated to maintaining the flexibility and reliability of power systems. This paper...

  16. Impact of roof integrated PV orientation on the residential electricity peak demand

    International Nuclear Information System (INIS)

    Sadineni, Suresh B.; Atallah, Fady; Boehm, Robert F.

    2012-01-01

    Highlights: ► A study to demonstrate peak load reductions at the substation. ► A new residential energy efficient community named Villa Trieste is being developed. ► The peak demand from the homes has decreased by 38% through energy efficiency. ► Orientation of roof integrated PV has less influence on the summer peak demand. ► Increasing thermostat temperature during peak by 1 °C can significantly reduce peaks. -- Abstract: Peak electricity demand has been an issue in the Desert Southwest region of the US, due to extreme summer temperatures. To address this issue, a consortium was formed between the University of Nevada, Las Vegas, Pulte Homes, and NV Energy. An energy efficient residential community was developed by the team in Las Vegas with approximately 200 homes to study substation-level peak reduction strategies. A summer peak reduction of more than 65%, between 1:00 PM and 7:00 PM, compared to code standard housing developments is the targeted goal of the project. Approximately 50 homes are already built and some are occupied. The energy performances of the homes have been monitored and are presented in this paper. Several peak electric load reduction strategies such as energy efficiency in buildings, roof integrated photovoltaics (PV) and direct load control have been applied. Though all the homes in the developed community are installed with 1.8 kW p PV systems, the orientation of the PV system depends on the building orientation. Focus of this paper is to find the impact of PV orientation on the peak load from a building. In addition, different time-of-use (TOU) energy pricing options are offered by the local electrical utility company. Hence it is important to find an optimal pricing option for each building. A computer model has been developed for one of the homes in the new development using building energy simulation code, ENERGY-10. Calculations on the PV orientations have shown that a south and 220° (i.e. 40° west of due south

  17. Meeting electricity demand in the United Kingdom in the eighties and beyond

    International Nuclear Information System (INIS)

    Lomer, D.R.

    The paper will describe the present system, its structure, the installed generating plant and fuel requirements. It will then discuss plants for the medium term, in general for the period 1980-1990. Future developments into the longer term (up to 2000) will be presented in broad terms setting out general views by the Department of Energy on all fuel demands and supplies, also expected electricity requirement, also the CEGB's views. A brief statement of possible coal, oil and gas supplies for the UK will be made. The basis of the agreed policy between Government and Industry to build 15 GW of nuclear plant in the next 10 years will be described. A view of the prospects for alternative energy supplies will be set out. The uncertainty of planning in the long term will be stressed and possible contingency plans described. (orig.) [de

  18. Electricity demand response in China: Status, feasible market schemes and pilots

    International Nuclear Information System (INIS)

    Li, Weilin; Xu, Peng; Lu, Xing; Wang, Huilong; Pang, Zhihong

    2016-01-01

    Demand Response (DR) has been extensively developed and implemented in the US and Europe. However, DR hardly exists in many developing countries for similar problems such as rigid power market and state monopoly. With the increasing imbalance between supply and demand in China's power industry, the government has issued new policies on DR and approved the first batch of pilot cities. China is setting a good example of how to encourage DR under monopolistic electric market and open up the market to aggregators and DR suppliers. This paper summarizes the current DR status, feasible DR market schemes and DR pilot projects in China. First, electric power system reform, renewable energy policies and power industry development are reviewed, highlighting the problems associated with the current dispatch mechanisms of DR policies and markets. New DR programs and DR-related policies are also introduced. On this basis, the driving forces and challenges associated with DR in China are analyzed. The major challenge is the lack of a suitable market mechanism for the current Chinese power industry. Hence, this paper presents six feasible strategies that fully utilize the existing policies. Additionally, the latest DR applications in different pilot cities are summarized and analyzed. - Highlights: • Summarize the status, feasible market schemes and pilot projects of DR in China. • Highlight the problems of the current dispatch mechanisms of DR policies and market. • Analyze the driving forces and challenges associated with DR in China. • Present six feasible strategies that fully utilize the existing policies. • Summarize and analyze the latest DR applications in different pilot cities.

  19. Hierarchical Load Tracking Control of a Grid-Connected Solid Oxide Fuel Cell for Maximum Electrical Efficiency Operation

    Directory of Open Access Journals (Sweden)

    Yonghui Li

    2015-03-01

    Full Text Available Based on the benchmark solid oxide fuel cell (SOFC dynamic model for power system studies and the analysis of the SOFC operating conditions, the nonlinear programming (NLP optimization method was used to determine the maximum electrical efficiency of the grid-connected SOFC subject to the constraints of fuel utilization factor, stack temperature and output active power. The optimal operating conditions of the grid-connected SOFC were obtained by solving the NLP problem considering the power consumed by the air compressor. With the optimal operating conditions of the SOFC for the maximum efficiency operation obtained at different active power output levels, a hierarchical load tracking control scheme for the grid-connected SOFC was proposed to realize the maximum electrical efficiency operation with the stack temperature bounded. The hierarchical control scheme consists of a fast active power control and a slower stack temperature control. The active power control was developed by using a decentralized control method. The efficiency of the proposed hierarchical control scheme was demonstrated by case studies using the benchmark SOFC dynamic model.

  20. Electricity supply industry modelling for multiple objectives under demand growth uncertainty

    International Nuclear Information System (INIS)

    Heinrich, G.; Basson, L.; Howells, M.; Petrie, J.

    2007-01-01

    Appropriate energy-environment-economic (E3) modelling provides key information for policy makers in the electricity supply industry (ESI) faced with navigating a sustainable development path. Key challenges include engaging with stakeholder values and preferences, and exploring trade-offs between competing objectives in the face of underlying uncertainty. As a case study we represent the South African ESI using a partial equilibrium E3 modelling approach, and extend the approach to include multiple objectives under selected future uncertainties. This extension is achieved by assigning cost penalties to non-cost attributes to force the model's least-cost objective function to better satisfy non-cost criteria. This paper incorporates aspects of flexibility to demand growth uncertainty into each future expansion alternative by introducing stochastic programming with recourse into the model. Technology lead times are taken into account by the inclusion of a decision node along the time horizon where aspects of real options theory are considered within the planning process. Hedging in the recourse programming is automatically translated from being purely financial, to include the other attributes that the cost penalties represent. From a retrospective analysis of the cost penalties, the correct market signals, can be derived to meet policy goal, with due regard to demand uncertainty. (author)

  1. Forecast analysis of the electricity supply-demand balance in France for summer 2013

    International Nuclear Information System (INIS)

    2013-05-01

    Under normal meteorological conditions, and notwithstanding localized risks associated with the vulnerability of certain regions, the forecast outlook for the electricity supply-demand balance in continental France shows no particular risk for the entire summer 2013 period. Special vigilance is maintained in the Provence-Alpes-Cote d'Azur region, given the risk of forest fires and potential outages affecting the dual 400 kV link from Toulon. This assessment is based on the assumption that forecast demand for summer 2013 will remain broadly stable as compared with summer 2012, given public economic indicators, but also that the forecast availability of the French generating fleet will increase by 1100 MW compared with summer 2012. This increased availability is based on information supplied by generators, and notably includes scheduled temporary outages of certain combined cycle gas turbines. Finally, growth in photovoltaic generation (3,700 MW of installed capacity currently in France) is continuing at a sustained pace, leading to a 700 MW increase in the mean availability rate for this generation technology as compared with summer 2012. Moreover, the substantial investments already made by RTE or currently in progress to develop its network (voltage support measures, Cotentin-Maine line, etc.) have had a very positive impact on the reliability of the power system. (authors)

  2. Spatial analysis of electricity demand patterns in Greece: Application of a GIS-based methodological framework

    Science.gov (United States)

    Tyralis, Hristos; Mamassis, Nikos; Photis, Yorgos N.

    2016-04-01

    We investigate various uses of electricity demand in Greece (agricultural, commercial, domestic, industrial use as well as use for public and municipal authorities and street lightning) and we examine their relation with variables such as population, total area, population density and the Gross Domestic Product. The analysis is performed on data which span from 2008 to 2012 and have annual temporal resolution and spatial resolution down to the level of prefecture. We both visualize the results of the analysis and we perform cluster and outlier analysis using the Anselin local Moran's I statistic as well as hot spot analysis using the Getis-Ord Gi* statistic. The definition of the spatial patterns and relationships of the aforementioned variables in a GIS environment provides meaningful insight and better understanding of the regional development model in Greece and justifies the basis for an energy demand forecasting methodology. Acknowledgement: This research has been partly financed by the European Union (European Social Fund - ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) - Research Funding Program: ARISTEIA II: Reinforcement of the interdisciplinary and/ or inter-institutional research and innovation (CRESSENDO project; grant number 5145).

  3. Short-term electricity demand and gas price forecasts using wavelet transforms and adaptive models

    International Nuclear Information System (INIS)

    Nguyen, Hang T.; Nabney, Ian T.

    2010-01-01

    This paper presents some forecasting techniques for energy demand and price prediction, one day ahead. These techniques combine wavelet transform (WT) with fixed and adaptive machine learning/time series models (multi-layer perceptron (MLP), radial basis functions, linear regression, or GARCH). To create an adaptive model, we use an extended Kalman filter or particle filter to update the parameters continuously on the test set. The adaptive GARCH model is a new contribution, broadening the applicability of GARCH methods. We empirically compared two approaches of combining the WT with prediction models: multicomponent forecasts and direct forecasts. These techniques are applied to large sets of real data (both stationary and non-stationary) from the UK energy markets, so as to provide comparative results that are statistically stronger than those previously reported. The results showed that the forecasting accuracy is significantly improved by using the WT and adaptive models. The best models on the electricity demand/gas price forecast are the adaptive MLP/GARCH with the multicomponent forecast; their NMSEs are 0.02314 and 0.15384 respectively. (author)

  4. An economic welfare analysis of demand response in the PJM electricity market

    International Nuclear Information System (INIS)

    Walawalkar, Rahul; Blumsack, Seth; Apt, Jay; Fernands, Stephen

    2008-01-01

    We analyze the economic properties of the economic demand-response (DR) program in the PJM electricity market in the United States using DR market data. PJM's program provided subsidies to customers who reduced load in response to price signals. The program incorporated a 'trigger point', at a locational marginal price of $75/MWh, at or beyond which payments for load reduction included a subsidy payment. Particularly during peak hours, such a program saves money for the system, but the subsidies involved introduce distortions into the market. We simulate demand-side bidding into the PJM market, and compare the social welfare gains with the subsidies paid to price-responsive load using load and price data for year 2006. The largest economic effect is wealth transfers from generators to non price-responsive loads. Based on the incentive payment structure that was in effect through the end of 2007, we estimate that the social welfare gains exceed the distortions introduced by the subsidies. Lowering the trigger point increases the transfer from generators to consumers, but may result in the subsidy outweighing the social welfare gains due to load curtailment. We estimate that the socially optimal range for the incentive trigger point would be $66-77/MWh

  5. Analyzing Capacity Withholding in Oligopoly Electricity Markets Considering Forward Contracts and Demand Elasticity

    Directory of Open Access Journals (Sweden)

    S. Salarkheili

    2011-12-01

    Full Text Available In this paper capacity withholding in an oligopolistic electricity market that all Generation Companies (GenCos bid in a Cournot model is analyzed and the capacity withheld index, the capacity distortion index and the price distortion index are obtained and formulated. Then a new index, Distortion-Withheld Index (DWI, is proposed in order to measure the potential ability of market for capacity withholding. In these indices the impact of demand elasticity on capacity withholding is considered and it is shown that demand elasticity plays an important role for capacity withholding and market power mitigation. Due to the significant role of forward contracts for market power mitigation and risk hedging in power markets, the impacts of these contracts on capacity withholding are considered. The effects of GenCos’ strategic forward contracts on capacity withholding are also discussed. Moreover, the relationship between capacity withholding of GenCos and market price distortion is acquired. A two-settlement market including a forward market and a spot market is used to describe GenCos’ strategic forward contracting and spot market competition.

  6. The strategies to develop renewable energy application in the frame to secure energy need and electricity demand in Indonesia

    International Nuclear Information System (INIS)

    Suharta, Herliyani; Hoetman, A. R.; Sayigh, A. m.

    2006-01-01

    The paper describe the evaluation of conventional energy usage and electricity condition in Indonesia. Also there is discussion on 14 facts that will affect the security in providing the electricity and other house hold energy demand. Those covers a picture of the growth of energy demand, oil subsidy, limited and remaining natural resources, crude petroleum export and import projection, forecast of un-risk natural gas production, gas and coal for electric generation, declining of coal deposit. An effort and considerations to increase the use of renewable energy (RE) are also described. It covers a power plant selection to mach the RE resources to partly fulfill the electricity development planning, its electricity price and also the use of RE resources to fulfill the energy need in household.(Author)

  7. Reconstruction of electrical impedance tomography (EIT) images based on the expectation maximum (EM) method.

    Science.gov (United States)

    Wang, Qi; Wang, Huaxiang; Cui, Ziqiang; Yang, Chengyi

    2012-11-01

    Electrical impedance tomography (EIT) calculates the internal conductivity distribution within a body using electrical contact measurements. The image reconstruction for EIT is an inverse problem, which is both non-linear and ill-posed. The traditional regularization method cannot avoid introducing negative values in the solution. The negativity of the solution produces artifacts in reconstructed images in presence of noise. A statistical method, namely, the expectation maximization (EM) method, is used to solve the inverse problem for EIT in this paper. The mathematical model of EIT is transformed to the non-negatively constrained likelihood minimization problem. The solution is obtained by the gradient projection-reduced Newton (GPRN) iteration method. This paper also discusses the strategies of choosing parameters. Simulation and experimental results indicate that the reconstructed images with higher quality can be obtained by the EM method, compared with the traditional Tikhonov and conjugate gradient (CG) methods, even with non-negative processing. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

  8. Optimal electricity dispatch on isolated mini-grids using a demand response strategy for thermal storage backup with genetic algorithms

    International Nuclear Information System (INIS)

    Neves, Diana; Silva, Carlos A.

    2015-01-01

    The present study uses the DHW (domestic hot water) electric backup from solar thermal systems to optimize the total electricity dispatch of an isolated mini-grid. The proposed approach estimates the hourly DHW load, and proposes and simulates different DR (demand response) strategies, from the supply side, to minimize the dispatch costs of an energy system. The case study consists on optimizing the electricity load, in a representative day with low solar radiation, in Corvo Island, Azores. The DHW backup is induced by three different demand patterns. The study compares different DR strategies: backup at demand (no strategy), pre-scheduled backup using two different imposed schedules, a strategy based on linear programming, and finally two strategies using genetic algorithms, with different formulations for DHW backup – one that assigns number of systems and another that assigns energy demand. It is concluded that pre-determined DR strategies may increase the generation costs, but DR strategies based on optimization algorithms are able to decrease generation costs. In particular, linear programming is the strategy that presents the lowest increase on dispatch costs, but the strategy based on genetic algorithms is the one that best minimizes both daily operation costs and total energy demand, of the system. - Highlights: • Integrated hourly model of DHW electric impact and electricity dispatch of isolated grid. • Proposal and comparison of different DR (demand response) strategies for DHW backup. • LP strategy presents 12% increase on total electric load, plus 5% on dispatch costs. • GA strategy presents 7% increase on total electric load, plus 8% on dispatch costs

  9. The dynamics of sectoral electricity demand for a panel of US states: New evidence on the consumption–growth nexus

    International Nuclear Information System (INIS)

    Saunoris, James W.; Sheridan, Brandon J.

    2013-01-01

    In this paper, we use a panel of the 48 contiguous US states over the period 1970–2009 to examine the dynamics of electricity demand in addressing the four hypotheses set forth in the literature: growth, conservation, neutrality, and feedback. In doing so we provide both short-run and long-run elasticity estimates for electricity demand. Recent developments in nonstationary panel estimation techniques allow for heterogeneity in the coefficients while examining the direction of causality among electricity consumption, electricity prices, and income growth. In addition to the full sample, we also disaggregate the sample into three sectors: commercial, industrial, and residential. The short-run results provide evidence in favor of the growth hypothesis for the aggregate sample, as well as for the industrial sector. For the residential and commercial sectors, the conservation hypothesis is supported. Long-run results favor the conservation hypothesis. To ascertain differences in electricity demand relating to electricity intensity we also examine states based on their efficiency in electricity consumption. Overall, the results yield in favor of the growth hypothesis for low intensity states and conservation hypothesis for high intensity states. - Highlights: • We use dynamic panel techniques to model electricity demand by sector for US states. • The conservation hypothesis is supported in the long run; short-run results are mixed. • The conservation hypothesis is supported in the high-electricity-intensity subsample. • The growth hypothesis is supported in the low-electricity-intensity subsample. • Policies aimed at energy conservation should be long-run in nature

  10. A New Methodology Based on Imbalanced Classification for Predicting Outliers in Electricity Demand Time Series

    Directory of Open Access Journals (Sweden)

    Francisco Javier Duque-Pintor

    2016-09-01

    Full Text Available The occurrence of outliers in real-world phenomena is quite usual. If these anomalous data are not properly treated, unreliable models can be generated. Many approaches in the literature are focused on a posteriori detection of outliers. However, a new methodology to a priori predict the occurrence of such data is proposed here. Thus, the main goal of this work is to predict the occurrence of outliers in time series, by using, for the first time, imbalanced classification techniques. In this sense, the problem of forecasting outlying data has been transformed into a binary classification problem, in which the positive class represents the occurrence of outliers. Given that the number of outliers is much lower than the number of common values, the resultant classification problem is imbalanced. To create training and test sets, robust statistical methods have been used to detect outliers in both sets. Once the outliers have been detected, the instances of the dataset are labeled accordingly. Namely, if any of the samples composing the next instance are detected as an outlier, the label is set to one. As a study case, the methodology has been tested on electricity demand time series in the Spanish electricity market, in which most of the outliers were properly forecast.

  11. Important Factors for Early Market Microgrids: Demand Response and Plug-in Electric Vehicle Charging

    Science.gov (United States)

    White, David Masaki

    Microgrids are evolving concepts that are growing in interest due to their potential reliability, economic and environmental benefits. As with any new concept, there are many unresolved issues with regards to planning and operation. In particular, demand response (DR) and plug-in electric vehicle (PEV) charging are viewed as two key components of the future grid and both will likely be active technologies in the microgrid market. However, a better understanding of the economics associated with DR, the impact DR can have on the sizing of distributed energy resource (DER) systems and how to accommodate and price PEV charging is necessary to advance microgrid technologies. This work characterizes building based DR for a model microgrid, calculates the DER systems for a model microgrid under DR through a minimization of total cost, and determines pricing methods for a PEV charging station integrated with an individual building on the model microgrid. It is shown that DR systems which consist only of HVAC fan reductions provide potential economic benefits to the microgrid through participation in utility DR programs. Additionally, peak shaving DR reduces the size of power generators, however increasing DR capacity does not necessarily lead to further reductions in size. As it currently stands for a microgrid that is an early adopter of PEV charging, current installation costs of PEV charging equipment lead to a system that is not competitive with established commercial charging networks or to gasoline prices for plug-in hybrid electric vehicles (PHEV).

  12. Distributed energy resources management using plug-in hybrid electric vehicles as a fuel-shifting demand response resource

    DEFF Research Database (Denmark)

    Morais, Hugo; Sousa, Tiago; Soares, J.

    2015-01-01

    In the smart grids context, distributed energy resources management plays an important role in the power systems' operation. Battery electric vehicles and plug-in hybrid electric vehicles should be important resources in the future distribution networks operation. Therefore, it is important...... to develop adequate methodologies to schedule the electric vehicles' charge and discharge processes, avoiding network congestions and providing ancillary services.This paper proposes the participation of plug-in hybrid electric vehicles in fuel shifting demand response programs. Two services are proposed......, namely the fuel shifting and the fuel discharging. The fuel shifting program consists in replacing the electric energy by fossil fuels in plug-in hybrid electric vehicles daily trips, and the fuel discharge program consists in use of their internal combustion engine to generate electricity injecting...

  13. An electric vehicle dispatch module for demand-side energy participation

    International Nuclear Information System (INIS)

    Zhou, Bowen; Yao, Feng; Littler, Tim; Zhang, Huaguang

    2016-01-01

    Highlights: • Real-time measurement and assessment to calculate EV initial state-of-charge (SOC). • Flexible EV charging allocation using measured available time duration (ATD). • Owner participation using mobile phone apps and a new EV dispatch module. • Online algorithm for real-time calculation of maximum and minimum adjustable limits. • Business-trading models with data security, trending and commercial impacts of EV. - Abstract: The penetration of the electric vehicle (EV) has increased rapidly in recent years mainly as a consequence of advances in transport technology and power electronics and in response to global pressure to reduce carbon emissions and limit fossil fuel consumption. It is widely acknowledged that inappropriate provision and dispatch of EV charging can lead to negative impacts on power system infrastructure. This paper considers EV requirements and proposes a module which uses owner participation, through mobile phone apps and on-board diagnostics II (OBD-II), for scheduled vehicle charging. A multi-EV reference and single-EV real-time response (MRS2R) online algorithm is proposed to calculate the maximum and minimum adjustable limits of necessary capacity, which forms part of decision-making support in power system dispatch. The proposed EV dispatch module is evaluated in a case study and the influence of the mobile app, EV dispatch trending and commercial impact is explored.

  14. Why Electricity Demand Is Highly Income-Elastic in Spain: A Cross-Country Comparison Based on an Index-Decomposition Analysis

    Directory of Open Access Journals (Sweden)

    Julián Pérez-García

    2017-03-01

    Full Text Available Since 1990, Spain has had one of the highest elasticities of electricity demand in the European Union. We provide an in-depth analysis into the causes of this high elasticity, and we examine how these same causes influence electricity demand in other European countries. To this end, we present an index-decomposition analysis of growth in electricity demand which allows us to identify three key factors in the relationship between gross domestic product (GDP and electricity demand: (i structural change; (ii GDP growth; and (iii intensity of electricity use. Our findings show that the main differences in electricity demand elasticities across countries and time are accounted for by the fast convergence in residential per capita electricity consumption. This convergence has almost concluded, and we expect the Spanish energy demand elasticity to converge to European standards in the near future.

  15. Generation Adequacy Report on the electricity supply-demand balance in France - 2005 Edition

    International Nuclear Information System (INIS)

    2006-01-01

    Under the terms of the Law of 10 February 2000, RTE is required to draw up a multi-annual Generation Adequacy Report on the electricity supply-demand balance in France. The present 2005 edition has been compiled in close conjunction with the working group in charge of long-term power generation pluri-annual investment programs at the French Directorate for Energy Demand and Markets, DIDEME. The purpose of RTE's Generation Adequacy Report is to quantify the additional electric generating facilities that need to be commissioned in the years ahead. It is based on various scenarios for the development of supply and demand, adopted on January 1, 2005, and covers the period 2006-2016. Three different consumption forecast scenarios have been used. All include a substantial drop in consumption by the Eurodif plant between 2010 and 2015. The two upper scenarios (called R1 and R2) fall within current trends, with annual growth of 1.7% and 1.5% until 2010 and a slowing down thereafter; they can be considered as equally likely to occur in the short-term. The low consumption growth scenario (R3) is intended to depict a context of environmental commitments. It is based on the assumption that demand side management initiatives will have an immediate impact, which makes it rather unlikely in the short-term. Under the reference scenario (R2), French domestic consumption, which was 468.5 TWh in 2004, reaches 508 TWh by 2010 and 552 TWh by 2020. Consumption at peak time in winter increases by around 1,000 MW per year. Up until 2016, France's fleet of generating facilities will be determined by a number of changes: the recommissioning of three of EDF's fuel-oil-fired units, the expected arrival of the EPR in 2012, and the definitive shutdown by 2015 of coal-fired plants that do not meet the requirements imposed by environmental regulations. In the field of renewable energy sources (RES), three different scenarios are considered. The main difference between them is the

  16. Designing an EU energy and climate policy portfolio for 2030: Implications of overlapping regulation under different levels of electricity demand

    International Nuclear Information System (INIS)

    Flues, Florens; Löschel, Andreas; Lutz, Benjamin Johannes; Schenker, Oliver

    2014-01-01

    The European Union's current climate and energy policy has to operate under an ex ante unforeseen economic crisis. As a consequence prices for carbon emission allowances in the EU Emissions Trading System collapsed. However, this price collapse may be amplified by the interaction of a carbon emission cap with supplementary policy targets such as minimum shares for renewables in the power sector. The static interaction between climate and renewable policies has been discussed extensively. This paper extends this debate by analysing the efficiency and effectiveness of a policy portfolio containing a cap and trade scheme and a target for a minimum renewable share in different states of aggregate electricity demand. Making use of a simple partial equilibrium model of the power sector we identify an asymmetric interaction of emissions trading and renewable quotas with respect to different states of aggregate electricity demand. The results imply that unintended consequences of the policy interaction may be particularly severe and costly when aggregate electricity demand is low and that carbon prices are more sensitive to changes in economic activity if they are applied in combination with renewable energy targets. Our analysis of the policy interaction focuses on the EU, yet the conclusions may also be of relevance for fast growing emerging economies like China. - Highlights: • A minimum renewable quota that is added to an existing emissions trading system causes excess costs. • Excess costs depend on electricity demand and are highest when electricity demand is low. • Excess costs can reach up to 1.2 Billion Euro annually in the European Union in 2030. • CO 2 prices are more sensitive to changes in electricity demand if combined with minimum renewable quota

  17. Electricity demand and supply scenarios for Maharashtra (India) for 2030: An application of long range energy alternatives planning

    International Nuclear Information System (INIS)

    Kale, Rajesh V.; Pohekar, Sanjay D.

    2014-01-01

    Forecasting of electricity demand has assumed a lot of importance to provide sustainable solutions to the electricity problems. LEAP has been used to forecast electricity demand for the target year 2030, for the state of Maharashtra (India). Holt’s exponential smoothing method has been used to arrive at suitable growth rates. Probable projections have been generated using uniform gross domestic product (GDP) growth rate and different values of elasticity of demands. Three scenarios have been generated which include Business as Usual (BAU), Energy Conservation (EC) and Renewable Energy (REN). Subsequent analysis on the basis of energy, environmental influence and cost has been done. In the target year 2030, the projected electricity demand for BAU and REN has increased by 107.3 per cent over the base year 2012 and EC electricity demand has grown by 54.3 per cent. The estimated values of green house gas (GHG) for BAU and EC, in the year 2030, are 245.2 per cent and 152.4 per cent more than the base year and for REN it is 46.2 per cent less. Sensitivity analysis has been performed to study the effect on the total cost of scenarios. Policy implications in view of the results obtained are also discussed. - Highlights: • Forecasted electricity scenarios by Long Range Energy Alternatives Planning (LEAP). • Critically analyzed the demand and supply prior to 2012 for a period of six years. • Used Holt’s exponential smoothing method ARIMA (0,1,1) for finding growth rates. • Devised suitable LEAP model for the generated scenarios. • Discussed policy implications for the generated scenarios

  18. Particle swarm optimization of driving torque demand decision based on fuel economy for plug-in hybrid electric vehicle

    International Nuclear Information System (INIS)

    Shen, Peihong; Zhao, Zhiguo; Zhan, Xiaowen; Li, Jingwei

    2017-01-01

    In this paper, an energy management strategy based on logic threshold is proposed for a plug-in hybrid electric vehicle. The plug-in hybrid electric vehicle powertrain model is established using MATLAB/Simulink based on experimental tests of the power components, which is validated by the comparison with the verified simulation model which is built in the AVL Cruise. The influence of the driving torque demand decision on the fuel economy of plug-in hybrid electric vehicle is studied using a simulation. The optimization method for the driving torque demand decision, which refers to the relationship between the accelerator pedal opening and driving torque demand, from the perspective of fuel economy is formulated. The dynamically changing inertia weight particle swarm optimization is used to optimize the decision parameters. The simulation results show that the optimized driving torque demand decision can improve the PHEV fuel economy by 15.8% and 14.5% in the fuel economy test driving cycle of new European driving cycle and worldwide harmonized light vehicles test respectively, using the same rule-based energy management strategy. The proposed optimization method provides a theoretical guide for calibrating the parameters of driving torque demand decision to improve the fuel economy of the real plug-in hybrid electric vehicle. - Highlights: • The influence of the driving torque demand decision on the fuel economy is studied. • The optimization method for the driving torque demand decision is formulated. • An improved particle swarm optimization is utilized to optimize the parameters. • Fuel economy is improved by using the optimized driving torque demand decision.

  19. Data and code for the exploratory data analysis of the electrical energy demand in the time domain in Greece.

    Science.gov (United States)

    Tyralis, Hristos; Karakatsanis, Georgios; Tzouka, Katerina; Mamassis, Nikos

    2017-08-01

    We present data and code for visualizing the electrical energy data and weather-, climate-related and socioeconomic variables in the time domain in Greece. The electrical energy data include hourly demand, weekly-ahead forecasted values of the demand provided by the Greek Independent Power Transmission Operator and pricing values in Greece. We also present the daily temperature in Athens and the Gross Domestic Product of Greece. The code combines the data to a single report, which includes all visualizations with combinations of all variables in multiple time scales. The data and code were used in Tyralis et al. (2017) [1].

  20. INDIA’S ELECTRICITY DEMAND FORECAST USING REGRESSION ANALYSIS AND ARTIFICIAL NEURAL NETWORKS BASED ON PRINCIPAL COMPONENTS

    Directory of Open Access Journals (Sweden)

    S. Saravanan

    2012-07-01

    Full Text Available Power System planning starts with Electric load (demand forecasting. Accurate electricity load forecasting is one of the most important challenges in managing supply and demand of the electricity, since the electricity demand is volatile in nature; it cannot be stored and has to be consumed instantly. The aim of this study deals with electricity consumption in India, to forecast future projection of demand for a period of 19 years from 2012 to 2030. The eleven input variables used are Amount of CO2 emission, Population, Per capita GDP, Per capita gross national income, Gross Domestic savings, Industry, Consumer price index, Wholesale price index, Imports, Exports and Per capita power consumption. A new methodology based on Artificial Neural Networks (ANNs using principal components is also used. Data of 29 years used for training and data of 10 years used for testing the ANNs. Comparison made with multiple linear regression (based on original data and the principal components and ANNs with original data as input variables. The results show that the use of ANNs with principal components (PC is more effective.

  1. Testing viability of cross subsidy using time-variant price elasticities of industrial demand for electricity: Indian experience

    International Nuclear Information System (INIS)

    Chattopadhyay, Pradip

    2007-01-01

    Indian electric tariffs are characterized by very high rates for industrial and commercial classes to permit subsidized electric consumption by residential and agricultural customers. We investigate the viability of this policy using monthly data for 1997-2003 on electric consumption by a few large industrial customers under the aegis of a small distribution company in the state of Uttar Pradesh. For a given price/cost ratio, it can be shown that if the cross-subsidizing class' electricity demand is sufficiently elastic, increasing the class' rates fail to recover incremental cross-subsidy necessary to support additional revenues for subsidized classes. This suboptimality is tested by individually estimating time-variant price-elasticities of demand for these industrial customers using Box-Cox and linear regressions. We find that at least for some of these customers, cross-subsidy was suboptimal prior to as late as October 2001, when rates were changed following reforms

  2. Testing viability of cross subsidy using time-variant price elasticities of industrial demand for electricity: Indian experience

    Energy Technology Data Exchange (ETDEWEB)

    Chattopadhyay, Pradip [New Hampshire Public Utilities Commission, 21 South Fruit Street, Suite 10, Concord NH 03301 (United States)]. E-mail: pradip.chattopadhyay@puc.nh.gov

    2007-01-15

    Indian electric tariffs are characterized by very high rates for industrial and commercial classes to permit subsidized electric consumption by residential and agricultural customers. We investigate the viability of this policy using monthly data for 1997-2003 on electric consumption by a few large industrial customers under the aegis of a small distribution company in the state of Uttar Pradesh. For a given price/cost ratio, it can be shown that if the cross-subsidizing class' electricity demand is sufficiently elastic, increasing the class' rates fail to recover incremental cross-subsidy necessary to support additional revenues for subsidized classes. This suboptimality is tested by individually estimating time-variant price-elasticities of demand for these industrial customers using Box-Cox and linear regressions. We find that at least for some of these customers, cross-subsidy was suboptimal prior to as late as October 2001, when rates were changed following reforms.

  3. Study of a thermoelectric system equipped with a maximum power point tracker for stand-alone electric generation.

    Science.gov (United States)

    Favarel, C.; Champier, D.; Bédécarrats, J. P.; Kousksou, T.; Strub, F.

    2012-06-01

    According to the International Energy Agency, 1.4 billion people are without electricity in the poorest countries and 2.5 billion people rely on biomass to meet their energy needs for cooking in developing countries. The use of cooking stoves equipped with small thermoelectric generator to provide electricity for basic needs (LED, cell phone and radio charging device) is probably a solution for houses far from the power grid. The cost of connecting every house with a landline is a lot higher than dropping thermoelectric generator in each house. Thermoelectric generators have very low efficiency but for isolated houses, they might become really competitive. Our laboratory works in collaboration with plane`te-bois (a non governmental organization) which has developed energy-efficient multifunction (cooking and hot water) stoves based on traditional stoves designs. A prototype of a thermoelectric generator (Bismuth Telluride) has been designed to convert a small part of the energy heating the sanitary water into electricity. This generator can produce up to 10 watts on an adapted load. Storing this energy in a battery is necessary as the cooking stove only works a few hours each day. As the working point of the stove varies a lot during the use it is also necessary to regulate the electrical power. An electric DC DC converter has been developed with a maximum power point tracker (MPPT) in order to have a good efficiency of the electronic part of the thermoelectric generator. The theoretical efficiency of the MMPT converter is discussed. First results obtained with a hot gas generator simulating the exhaust of the combustion chamber of a cooking stove are presented in the paper.

  4. Controlling the demand for electricity: strategies and challenges in the residential sector of the OECD countries

    International Nuclear Information System (INIS)

    Lebot, B.

    2003-01-01

    By reinforcing policies to improve the energy efficiency of household appliances (particularly by rating the efficiency of each appliance as a minimum of its overall cost from 2005 onwards), the member countries of the IEA are in a position to reduce their annual CO 2 emissions by approximately 322 million tonnes (Mt) by 2010, compared to what they would have obtained using current policies. In 2030, this same policy will make it possible to achieve an annual saving of 1 110 TWh in the consumption of electricity, (572 Mt of CO 2 each year). This measure alone will meet 30% of the objectives of the member countries of the IEA under the Kyoto agreements concerning climatic change. These reductions can be obtained at a negative cost for society as the additional cost generated by improvements in energy efficiency is offset by savings made in operating costs during the life of the appliance. Thus, in the United States, each tonne of CO 2 saved in this way in 2020 will generate $65 for society. In Europe, every tonne of CO 2 saved will generate a gain of euros 169 (the difference being accounted for by the higher cost of electricity and by lower energy efficiency standards currently existing in Europe). It is possible to make major savings in all regions of the OECD, despite the vast diversity of the various situations of the countries. In the member countries of the IEA, the policies in place have already demonstrated their economic effectiveness in reducing demand for energy and greenhouse gas emissions. Up to 2000, they made it possible to reduce greenhouse gas emissions by approximately 46 Mt of CO 2 each year. These policies will contribute to reducing emissions by 126 Mt of CO 2 each year up to 2010. International co-operation offers real advantages in the deployment of policies for controlling the demand for energy by households. Manufacturers, consumers and governments all benefit from greater transparency in the marketplace, improved comparisons of test methods

  5. The electricity supply-demand balance for the winter of 2014-2015. Press kit - November 7, 2014

    International Nuclear Information System (INIS)

    2014-01-01

    Twice a year, RTE publishes a forecast study of the electricity supply and demand in continental France for the summer and winter periods. The study is based on the information supplied by electric utilities concerning the expected availability of power generation means and on statistical meteorological models. Safety margins are calculated using thousands of probabilistic scenarios combining various production and consumption situations. This report is the forecast study for the winter of 2014-2015

  6. Analysis of the electricity supply-demand balance during the winter of 2008-2009: moderate risk of supply disruption

    International Nuclear Information System (INIS)

    2008-10-01

    Twice a year, RTE publishes a forecast study of the electricity supply and demand in continental France for the summer and winter periods. The study is based on the information supplied by electric utilities concerning the expected availability of power generation means and on statistical meteorological models. Safety margins are calculated using thousands of probabilistic scenarios combining various production and consumption situations. This report is the forecast study for the winter of 2008-2009

  7. Summer 2011 forecast analysis. Forecast analysis of the electricity supply-demand balance in France for the summer of 2011

    International Nuclear Information System (INIS)

    2011-06-01

    Twice a year, RTE publishes a forecast study of the electricity supply and demand in continental France for the summer and winter periods. The study is based on the information supplied by electric utilities concerning the expected availability of power generation means and on statistical meteorological models. Safety margins are calculated using thousands of probabilistic scenarios combining various production and consumption situations. This report is the forecast study for the summer of 2011

  8. Generation Adequacy Report on the electricity supply-demand balance in France - 2017 Edition. Reference document

    International Nuclear Information System (INIS)

    2018-01-01

    In accordance with French legislation, each year RTE drafts and publishes the 'Generation Adequacy Report' concerning the supply demand balance of electricity. As a diagnostic reference for security of supply and of the electric network, the report is a key corporate exercise which is used to shed light on the medium to long term forecasts for security of supply, and therefore to develop national energy policies. This 2017 report presents: 1 - the power consumption and its perspectives according to the correct implementation of energy efficiency actions; 2 - the power generation park with scenarios integrating a public control and a modeling of the economic decisions of competing actors; 3 - A realistic European power trade vision integrating energy policy uncertainties of neighboring countries; 4 - The five next year analysis: a tight balance with necessary choices; 5 - the 'Ohm' scenario: an unprecedented adaptation of the production park to meet the nuclear share law goal; 6 - The 'Ampere' scenario for a reduction of nuclear production following the rhythm of renewable energy sources development; 7 - The 'Hertz' scenario with a development of thermal means to accelerate the nuclear phasing out without CO 2 emissions increase; 8 - The 'Volt' scenario for a sustained development of renewable energy sources together with an evolution of the nuclear park adapted to the European economic opportunities; 9 - The 'Watt' scenario for an automatic decommissioning of reactors after 40 years of operation; 10 - Self-consumption development and the transformation of the power system under the effect of investment decision decentralization; 11 - Cross-analysis of scenarios: the 2030-2035 power system has to be decided today

  9. Distributed Energy Systems Integration and Demand Optimization for Autonomous Operations and Electric Grid Transactions

    Energy Technology Data Exchange (ETDEWEB)

    Ghatikar, Girish [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Greenlots, San Francisco, CA (United States); Mashayekh, Salman [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Stadler, Michael [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Center for Energy and Innovation Technologies (Austria); Yin, Rongxin [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Liu, Zhenhua [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2015-11-29

    Distributed power systems in the U.S. and globally are evolving to provide reliable and clean energy to consumers. In California, existing regulations require significant increases in renewable generation, as well as identification of customer-side distributed energy resources (DER) controls, communication technologies, and standards for interconnection with the electric grid systems. As DER deployment expands, customer-side DER control and optimization will be critical for system flexibility and demand response (DR) participation, which improves the economic viability of DER systems. Current DER systems integration and communication challenges include leveraging the existing DER and DR technology and systems infrastructure, and enabling optimized cost, energy and carbon choices for customers to deploy interoperable grid transactions and renewable energy systems at scale. Our paper presents a cost-effective solution to these challenges by exploring communication technologies and information models for DER system integration and interoperability. This system uses open standards and optimization models for resource planning based on dynamic-pricing notifications and autonomous operations within various domains of the smart grid energy system. It identifies architectures and customer engagement strategies in dynamic DR pricing transactions to generate feedback information models for load flexibility, load profiles, and participation schedules. The models are tested at a real site in California—Fort Hunter Liggett (FHL). Furthermore, our results for FHL show that the model fits within the existing and new DR business models and networked systems for transactive energy concepts. Integrated energy systems, communication networks, and modeling tools that coordinate supply-side networks and DER will enable electric grid system operators to use DER for grid transactions in an integrated system.

  10. Peak electricity demand and social practice theories: Reframing the role of change agents in the energy sector

    International Nuclear Information System (INIS)

    Strengers, Yolande

    2012-01-01

    Demand managers currently draw on a limited range of psychology and economic theories in order to shift and shed peak electricity demand. These theories place individual consumers and their attitudes, behaviours and choices at the centre of the problem. This paper reframes the issue of peak electricity demand using theories of social practices, contending that the ‘problem’ is one of transforming, technologically-mediated social practices. It reflects on how this body of theory repositions and refocuses the roles and practices of professions charged with the responsibility and agency for affecting and managing energy demand. The paper identifies three areas where demand managers could refocus their attention: (i) enabling co-management relationships with consumers; (ii) working beyond their siloed roles with a broader range of human and non-human actors; and (iii) promoting new practice ‘needs’ and expectations. It concludes by critically reflecting on the limited agency attributed to ‘change agents’ such as demand managers in dominant understandings of change. Instead, the paper proposes the need to identify and establish a new group of change agents who are actively but often unwittingly involved in reconfiguring the elements of problematic peaky practices. - Highlights: ► I reframe peak electricity demand as a problem of changing social practices. ► Micro-grids, and dynamic pricing reorient household routines and enable co-management. ► Infrastructures inside and outside the home configure peaky practices. ► Demand managers are encouraged to promote and challenge consumer ‘needs’. ► I identify a new group of change agents implicated in peaky practices.

  11. Electricity demand and spot price forecasting using evolutionary computation combined with chaotic nonlinear dynamic model

    International Nuclear Information System (INIS)

    Unsihuay-Vila, C.; Zambroni de Souza, A.C.; Marangon-Lima, J.W.; Balestrassi, P.P.

    2010-01-01

    This paper proposes a new hybrid approach based on nonlinear chaotic dynamics and evolutionary strategy to forecast electricity loads and prices. The main idea is to develop a new training or identification stage in a nonlinear chaotic dynamic based predictor. In the training stage five optimal parameters for a chaotic based predictor are searched through an optimization model based on evolutionary strategy. The objective function of the optimization model is the mismatch minimization between the multi-step-ahead forecasting of predictor and observed data such as it is done in identification problems. The first contribution of this paper is that the proposed approach is capable of capturing the complex dynamic of demand and price time series considered resulting in a more accuracy forecasting. The second contribution is that the proposed approach run on-line manner, i.e. the optimal set of parameters and prediction is executed automatically which can be used to prediction in real-time, it is an advantage in comparison with other models, where the choice of their input parameters are carried out off-line, following qualitative/experience-based recipes. A case study of load and price forecasting is presented using data from New England, Alberta, and Spain. A comparison with other methods such as autoregressive integrated moving average (ARIMA) and artificial neural network (ANN) is shown. The results show that the proposed approach provides a more accurate and effective forecasting than ARIMA and ANN methods. (author)

  12. A scoping study: demand side measures on the UK electrical system

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2005-07-01

    The study is intended to eventually bring about a number of improvements in the UK electrical system, particularly in regard to Demand Side Management (DSM). Among the benefits envisaged are (a) increased security of supply when the network is under stress; (b) reduction in costs; (c) simpler outage management; (d) carbon saving and (e) increased energy efficiency. So far, these potential benefits have attracted little attention in the residential and small business sectors of the market: suggested reasons for this are listed. Taking into account the experience of other countries, three options are presented for a UK DSM programme: they are (i) customer initiated; (ii) supplier initiated and (iii) distributor initiated. At present, all the suggested options need further study and to aid the development for small customers, five possible initiatives are suggested. This final report (95 pages) includes a detailed description of the research required and a tender process for a customer-initiated programme. The report was prepared by KEMA Limited under contract to the DTI.

  13. Impact Analysis of Customized Feedback Interventions on Residential Electricity Load Consumption Behavior for Demand Response

    Directory of Open Access Journals (Sweden)

    Fei Wang

    2018-03-01

    Full Text Available Considering the limitations of traditional energy-saving policies, a kind of energy conservation method called the Information Feedback to Residential Electricity Load Customers, which could impact the demand response capacity, has increasingly received more attention. However, most of the current feedback programs provide the same feedback information to all customers regardless of their diverse characteristics, which may reduce the energy-saving effects or even backfire. This paper attempts to investigate how different types of customers may change their behaviors under a set of customized feedback. We conducted a field survey study in Qinhuangdao (QHD, China. First, we conducted semi-structured interviews to classify four groups of customers of different energy-saving awareness, energy-saving potential, and behavioral variability. Then, 156 QHD households were surveyed using scenarios to collect feedback of different scenarios. Social science theories were used to guide the discussion on the behavior changes as a result of different feedback strategies and reveal the reasons for customers’ behaviors. Using the Chi-Square test of independence, the variables that have strong correlations with the categories of residents are extracted to provide references for residents’ classification. Finally, the practical implications and needs for future research are discussed.

  14. A scoping study: demand side measures on the UK electrical system

    International Nuclear Information System (INIS)

    2005-01-01

    The study is intended to eventually bring about a number of improvements in the UK electrical system, particularly in regard to Demand Side Management (DSM). Among the benefits envisaged are (a) increased security of supply when the network is under stress; (b) reduction in costs; (c) simpler outage management; (d) carbon saving and (e) increased energy efficiency. So far, these potential benefits have attracted little attention in the residential and small business sectors of the market: suggested reasons for this are listed. Taking into account the experience of other countries, three options are presented for a UK DSM programme: they are (i) customer initiated; (ii) supplier initiated and (iii) distributor initiated. At present, all the suggested options need further study and to aid the development for small customers, five possible initiatives are suggested. This final report (95 pages) includes a detailed description of the research required and a tender process for a customer-initiated programme. The report was prepared by KEMA Limited under contract to the DTI

  15. A Study of Demand Response Effect of Thermal Storage Air-Conditioning Systems in Consideration of Electricity Market Prices

    Science.gov (United States)

    Omagari, Yuko; Sugihara, Hideharu; Tsuji, Kiichiro

    This paper evaluates the economic impact of the introduction of customer-owned Thermal Storage Air-conditioning (TSA) systems, in an electricity market, from the viewpoint of the load service entity. We perform simulations on the condition that several thousand customers install TSA systems and shift peak demand in an electricity market by one percent. Our numerical results indicate that the purchase cost of the LSE was reduced through load management of customers with TSA systems. The introduction of TSA systems also reduced the volatility of market clearing price and reduced the whole-trade cost in an electricity market.

  16. Management and control of the electrical energy demand; Administracion y control de la demanda de la energia electrica

    Energy Technology Data Exchange (ETDEWEB)

    Johnson Controls [Comision Federal de Electricidad (Mexico)

    2005-07-01

    Administrative measures allow a reduction in the energy consumption, but not always in the electrical demand. Control measures allow a reduction in the billing of the electrical demand, but not always in the energy consumption. This is why it is explained in this document what management and control of the electrical demand is, as well as its control strategies, the control alternatives, the billing demand and at the same time graphical representations along with three practical cases on the management of demand in air compressors, air conditioning equipment and in corporative buildings are presented. [Spanish] La aplicacion de las medidas administrativas permite reducir el consumo de energia, pero no siempre la demanda electrica. La aplicacion de medidas de control permiten reducir la demanda electrica facturable, pero no siempre el consumo de energia. Es por eso que en este documento se explica que es la administracion y el control de la demanda electrica, sus estrategias de control, las alternativas de control, la demanda facturable, representaciones graficas y tres casos practicos sobre la administracion de demanda en compresores de aire, la administracion de demanda en aire acondicionado y la administracion de demanda en un edificio corporativo.

  17. Application of battery-based storage systems in household-demand smoothening in electricity-distribution grids

    International Nuclear Information System (INIS)

    Purvins, Arturs; Papaioannou, Ioulia T.; Debarberis, Luigi

    2013-01-01

    Highlights: ► Battery system application in demand smoothening in distribution grids is analysed. ► Five European countries are studied with and without high photovoltaic deployment. ► A sensitivity analysis for different battery system parameters is performed. ► A simple battery system management is sufficient for low demand smoothening. ► More elaborate management is required for high demand smoothening. - Abstract: This article analyses in technical terms the application of battery-based storage systems for household-demand smoothening in electricity-distribution grids. The analysis includes case studies of Denmark, Portugal, Greece, France and Italy. A high penetration of photovoltaic systems in distribution grids is considered as an additional scenario. A sensitivity analysis is performed in order to examine the smoothening effect of daily demand profiles for different configurations of the battery system. In general, battery-storage systems with low rated power and low battery capacity can smooth the demand sufficiently with the aid of a simple management process. For example, with 1 kW of peak demand, a 30–45% decrease in the variability of the daily demand profile can be achieved with a battery system of 0.1 kW rated power and up to 0.6 kW h battery capacity. However, further smoothening requires higher battery-system capacity and power. In this case, more elaborate management is also needed to use the battery system efficiently.

  18. Industrial and residential electricity demand dynamics in Japan: How did price and income elasticities evolve from 1989 to 2014?

    International Nuclear Information System (INIS)

    Wang, Nan; Mogi, Gento

    2017-01-01

    This study estimates the price and income elasticities of industrial and residential electricity demand in Japan with the annual data from 1989 to 2014. A time varying parameter (TVP) model with the Kalman filter is applied to monitor the evolution of consumer behaviors in the “post-bubble” period given the exogenous shock (financial crisis in 2008) and the structural breaks (electricity deregulation and Fukushima Daiichi crisis). The TVP model can provide a robust estimation of elasticities and can detect the outliers and the structural breaks. The results suggest that both industrial and residential consumers become less sensitive to price after the electricity deregulation and the financial crisis, and more sensitive to price after the Fukushima Daiichi crisis. Especially the industrial sector is less sensitive to price after the retail deregulation. By contrast, the income elasticities of industrial and residential sector consumers are stable during the examined period. Results also indicate that a negative relationship exists between the price elasticity of electricity demand and the price level of electricity after the electric sector deregulation. Some insights on the further electric sector reform and the environmental taxation in Japan are also provided. - Highlights: • A time varying parameter model is calculated with the Kalman filter. • Income elasticities are stable while price elasticities are time-varying. • Industrial sector is less sensitive to price change than residential sector. • Negative relationship between price elasticity and price level is found.

  19. A demand-side approach to the optimal deployment of electric vehicle charging stations in metropolitan areas

    International Nuclear Information System (INIS)

    Andrenacci, N.; Ragona, R.; Valenti, G.

    2016-01-01

    Highlights: • A demand-side approach to the location of charging infrastructure problem is discussed in the paper. • The analysis is based on a large data-set of private vehicle travels within the urban area of Rome. • Cluster analysis is applied to the data to find the optimal location zones for charging infrastructures. • The daily energy demand and the average number of users per day are calculated for each and every charging infrastructure. - Abstract: Despite all the acknowledged advantages in terms of environmental impact reduction, energy efficiency and noise reduction, the electric mobility market is below expectations. In fact, electric vehicles have limitations that pose several important challenges for achieving a sustainable mobility system: among them, the availability of an adequate charging infrastructure is recognized as a fundamental requirement and appropriate approaches to optimize public and private investments in this field are to be delineated. In this paper we consider actual data on conventional private vehicle usage in the urban area of Rome to carry out a strategy for the optimal allocation of charging infrastructures into portions (subareas) of the urban area, based on an analysis of a driver sample under the assumption of a complete switch to an equivalent fleet of electric vehicles. Moreover, the energy requirement for each one of the subareas is estimated in terms of the electric energy used by the equivalent fleet of electric vehicles to reach their destination. The model can be easily generalized to other problems regarding facility allocation based on user demand.

  20. An Economic Evalution of Demand-side Energy Storage Systems by using a Multi-agent based Electricity Market

    Science.gov (United States)

    Furusawa, Ken; Sugihara, Hideharu; Tsuji, Kiichiro

    Opened wholesale electric power market in April 2005, deregulation of electric power industry in Japan has faced a new competitive environment. In the new environment, Independent Power Producer (: IPP), Power Producer and Supplier (: PPS), Load Service Entity (: LSE) and electric utility can trade electric energy through both bilateral contracts and single-price auction at the electricity market. In general, the market clearing price (: MCP) is largely changed by amount of total load demand in the market. The influence may cause price spike, and consequently the volatility of MCP will make LSEs and their customers to face a risk of revenue and cost. DSM is attracted as a means of load leveling, and has effect on decreasing MCP at peak load period. Introducing Energy Storage systems (: ES) is one of DSM in order to change demand profile at customer-side. In case that customers decrease their own demand at jumped MCP, a bidding strategy of generating companies may be changed their strategy. As a result, MCP is changed through such complex mechanism. In this paper the authors evaluate MCP by multi-agent. It is considered that customer-side ES has an effect on MCP fluctuation. Through numerical examples, this paper evaluates the influence on MCP by controlling customer-side ES corresponding to variation of MCP.

  1. Incentive-based demand response programs designed by asset-light retail electricity providers for the day-ahead market

    International Nuclear Information System (INIS)

    Fotouhi Ghazvini, Mohammad Ali; Faria, Pedro; Ramos, Sergio; Morais, Hugo; Vale, Zita

    2015-01-01

    Following the deregulation experience of retail electricity markets in most countries, the majority of the new entrants of the liberalized retail market were pure REP (retail electricity providers). These entities were subject to financial risks because of the unexpected price variations, price spikes, volatile loads and the potential for market power exertion by GENCO (generation companies). A REP can manage the market risks by employing the DR (demand response) programs and using its' generation and storage assets at the distribution network to serve the customers. The proposed model suggests how a REP with light physical assets, such as DG (distributed generation) units and ESS (energy storage systems), can survive in a competitive retail market. The paper discusses the effective risk management strategies for the REPs to deal with the uncertainties of the DAM (day-ahead market) and how to hedge the financial losses in the market. A two-stage stochastic programming problem is formulated. It aims to establish the financial incentive-based DR programs and the optimal dispatch of the DG units and ESSs. The uncertainty of the forecasted day-ahead load demand and electricity price is also taken into account with a scenario-based approach. The principal advantage of this model for REPs is reducing the risk of financial losses in DAMs, and the main benefit for the whole system is market power mitigation by virtually increasing the price elasticity of demand and reducing the peak demand. - Highlights: • Asset-light electricity retail providers subject to financial risks. • Incentive-based demand response program to manage the financial risks. • Maximizing the payoff of electricity retail providers in day-ahead market. • Mixed integer nonlinear programming to manage the risks

  2. Maximum capacity model of grid-connected multi-wind farms considering static security constraints in electrical grids

    International Nuclear Information System (INIS)

    Zhou, W; Oodo, S O; He, H; Qiu, G Y

    2013-01-01

    An increasing interest in wind energy and the advance of related technologies have increased the connection of wind power generation into electrical grids. This paper proposes an optimization model for determining the maximum capacity of wind farms in a power system. In this model, generator power output limits, voltage limits and thermal limits of branches in the grid system were considered in order to limit the steady-state security influence of wind generators on the power system. The optimization model was solved by a nonlinear primal-dual interior-point method. An IEEE-30 bus system with two wind farms was tested through simulation studies, plus an analysis conducted to verify the effectiveness of the proposed model. The results indicated that the model is efficient and reasonable.

  3. Maximum capacity model of grid-connected multi-wind farms considering static security constraints in electrical grids

    Science.gov (United States)

    Zhou, W.; Qiu, G. Y.; Oodo, S. O.; He, H.

    2013-03-01

    An increasing interest in wind energy and the advance of related technologies have increased the connection of wind power generation into electrical grids. This paper proposes an optimization model for determining the maximum capacity of wind farms in a power system. In this model, generator power output limits, voltage limits and thermal limits of branches in the grid system were considered in order to limit the steady-state security influence of wind generators on the power system. The optimization model was solved by a nonlinear primal-dual interior-point method. An IEEE-30 bus system with two wind farms was tested through simulation studies, plus an analysis conducted to verify the effectiveness of the proposed model. The results indicated that the model is efficient and reasonable.

  4. Demand Profile Study of Battery Electric Vehicle under Different Charging Options

    DEFF Research Database (Denmark)

    Marra, Francesco; Yang, Guang Ya; Træholt, Chresten

    2012-01-01

    An increased research on electric vehicles (EV) and plug-in hybrid electric vehicles (PHEV) deals with their flexible use in electric power grids. Several research projects on smart grids and electric mobility are now looking into realistic models representing the behavior of an EV during charging...

  5. Distributed energy resources management using plug-in hybrid electric vehicles as a fuel-shifting demand response resource

    International Nuclear Information System (INIS)

    Morais, H.; Sousa, T.; Soares, J.; Faria, P.; Vale, Z.

    2015-01-01

    Highlights: • Definition fuel shifting demand response programs applied to the electric vehicles. • Integration of the proposed fuel shifting in energy resource management algorithm. • Analysis of fuel shifting contribution to support the consumption increasing. • Analysis of fuel shifting contribution to support the electric vehicles growing. • Sensitivity analysis considering different electric vehicles penetration levels. - Abstract: In the smart grids context, distributed energy resources management plays an important role in the power systems’ operation. Battery electric vehicles and plug-in hybrid electric vehicles should be important resources in the future distribution networks operation. Therefore, it is important to develop adequate methodologies to schedule the electric vehicles’ charge and discharge processes, avoiding network congestions and providing ancillary services. This paper proposes the participation of plug-in hybrid electric vehicles in fuel shifting demand response programs. Two services are proposed, namely the fuel shifting and the fuel discharging. The fuel shifting program consists in replacing the electric energy by fossil fuels in plug-in hybrid electric vehicles daily trips, and the fuel discharge program consists in use of their internal combustion engine to generate electricity injecting into the network. These programs are included in an energy resources management algorithm which integrates the management of other resources. The paper presents a case study considering a 37-bus distribution network with 25 distributed generators, 1908 consumers, and 2430 plug-in vehicles. Two scenarios are tested, namely a scenario with high photovoltaic generation, and a scenario without photovoltaic generation. A sensitivity analyses is performed in order to evaluate when each energy resource is required

  6. On the Mobile Communication Requirements for the Demand-Side Management of Electric Vehicles

    Directory of Open Access Journals (Sweden)

    Stefano Rinaldi

    2018-05-01

    Full Text Available The rising concerns about global warming and environmental pollution are increasingly pushing towards the replacement of road vehicles powered by Internal Combustion Engines (ICEs. Electric Vehicles (EVs are generally considered the best candidates for this transition, however, existing power grids and EV management systems are not yet ready for a large penetration of EVs, and the current opinion of the scientific community is that further research must be done in this field. The so-called Vehicle-to-Grid (V2G concept plays a relevant role in this scenario by providing the communication capabilities required by advanced control and Demand-Side Management (DSM strategies. Following this research trend, in this paper the communication requirements for the DSM of EVs in urban environments are discussed, by focusing on the mobile communication among EVs and smart grids. A specific system architecture for the DSM of EVs moving inside urban areas is proposed and discussed in terms of the required data throughput. In addition, the use of a Low-Power Wide-Area Network (LPWAN solution—the Long-Range Wide Area Network (LoRaWAN technology—is proposed as a possible alternative to cellular-like solutions, by testing an experimental communication infrastructure in a real environment. The results show that the proposed LPWAN technology is capable to handle an adequate amount of information for the considered application, and that one LoRa base station is able to serve up to 438 EVs per cell, and 1408 EV charging points.

  7. Consequences of EU enlargement for supply and demand in the electricity market with special emphasis on nuclear power

    International Nuclear Information System (INIS)

    Jaeger, G.

    2004-01-01

    After the enlargement of the European Union, Europe has acquired a new dimension which is reflected also on the electricity market. The aggregate European electricity requirement of 3 000 TWh in Europe constitutes approximately one quarter of the world electricity generation. Nuclear power contributes a major share of 966 TWh. In electricity generation from nuclear power, EU-25 is No. 1 in the world. The rising demand for electricity cannot be met by the existing power plant park in the next few decades. Insufficient possibilities of exchange among countries and, especially, the enormous requirement to replace more than 200,000 MW of electricity generating capacity in Europe by 2020, plus another 100,000 MW arising from growing demand, make a comprehensive renewal of the European power plant park indispensable. After the EU enlargement, the standards of the ''old'' European Union are the yardstick for the entire ''new'' Union. This gives rise to enormous efforts, especially in the accession countries, to curb emissions and increase safety. The need for modern power plant technology is becoming particularly apparent in these cases. The example of the ten new member countries clearly shows the options realistically available for electricity generation in the future and indispensable for a favorable infrastructure. The conventional energy resources, i. e. coal, gas, and nuclear power, will be the main sources of electricity generation in Europe over the next few decades. This finding does not meet the expectations of many members of the public who feel that renewables would make the largest contribution to power supply in twenty years' time. This makes it imperative to regain popular acceptance in order to ensure electricity generation at favorable conditions and at a high level of environmental protection in the whole of Europe, with enough leeway to further advance the expansion of renewables and support a positive economic development of Europe. (orig.)

  8. Development of a “Current Energy Mix Scenario” and a “Electricity as Main Energy Source Scenario” for electricity demand up to 2100

    Directory of Open Access Journals (Sweden)

    Mário J. S. Brito

    2014-06-01

    Full Text Available In this work, we develop a model to forecast world electricity production up to 2100. We analyze historical data for electricity production, population and GDP per Capita for the period 1900–2008. We show that electricity production follows general trends. First, there is an electricity intensity target of 0.20-0.25 kWh per unit of GDP (US$2012 as economies mature, except in countries traditionally relying heavily on renewable electricity (hydroelectricity, for whom this target ranges between 0.50 to 0.80 kWh per unit GDP. Also, countries that belong to the same region tend to follow the evolution of electricity production and GDP/Capita of a regional “modelcountry”. Equations that describe the behavior of these model countries are used to forecast electricity production per capita up to 2100 under a low and a high scenario for the evolution of GDP per Capita. For electricity production two main scenarios were set: “Current Energy MixScenario” and “Electricity as Main Energy Source Scenario”, with two additional sub scenarios considering slightly different electric intensities. Forecasts up to 2100 yield a demand forelectricity production 3.5 to 5 times higher than the current production for the “Current EnergyMix Scenario” and about 9 to 14 times for the “Electricity as Main Energy Source Scenario”. Forecasts for the “Current Energy Mix Scenario” matched well with forecasts from IEA/EIA (International Energy Agency/ Energy Information Administration while the forecasts for the“Electricity as the Main Energy Source Scenario” are much higher than current predictions.

  9. Modeling framework for estimating impacts of climate change on electricity demand at regional level: Case of Greece

    International Nuclear Information System (INIS)

    Mirasgedis, S.; Sarafidis, Y.; Georgopoulou, E.; Kotroni, V.; Lagouvardos, K.; Lalas, D.P.

    2007-01-01

    This paper focuses on the potential upcoming impacts of climate change in the 21st century on electricity demand at regional/national levels for regions where topography and location result in large differences in local climate. To address this issue, a regional climate model, PRECIS, has been used to predict future climatic conditions under different emissions scenarios (namely A2 and B2 of the IPCC special report on emissions scenarios (SRES)) as an input to a multiple regression model of the sensitivity of electricity demand in the Greek interconnected power system to climate and socio-economic factors. The economic development input to the multiple regression model follows the same storylines of the SRES scenarios upto 2100 and includes sub-scenarios to cover larger and smaller economic development rates. The results of the analysis indicate an increase of the annual electricity demand attributable solely to climate change of 3.6-5.5% under all scenarios examined, most of which results from increased annual variability with substantial increases during the summer period that outweighs moderate declines estimated for the winter period. This becomes more pronounced if inter-annual variability, especially of summer months, is taken into consideration. It was also found that in the long run, economic development will have a strong effect on future electricity demand, thus increasing substantially the total amount of energy consumed for cooling and heating purposes. This substantial increase in energy demand with strong annual variability will lead to the need for inordinate increases of installed capacity, a large percentage of which will be under utilized. Thus, appropriate adaptation strategies (e.g. new investments, interconnections with other power systems, energy saving programmes, etc.) need to be developed at the state level in order to ensure the security of energy supply. (author)

  10. Estimation of Future Demand for Neutron-Transmutation-Doped Silicon Caused by Development of Hybrid Electric Vehicle

    International Nuclear Information System (INIS)

    Kim, Myong Seop; Park, Sang Jun

    2008-01-01

    By using this doping method, silicon semiconductors with an extremely uniform dopant distribution can be produced. They are usually used for high power devices such as thyristor (SCR), IGBT, IGCT and GTO. Now, the demand for high power semiconductor devices has increased rapidly due to the rapid increase of the green energy technologies. Among them, the productions of hybrid cars or fuel cell engines are excessively increased to reduce the amount of discharged air pollution substances, such as carbon dioxide which causes global warming. It is known that the neutron-transmutation-doped floating-zone (FZ) silicon wafers are used in insulated-gate bipolar transistors (IGBTs) which control the speed of the electric traction motors equipped in hybrid or fuel cell vehicles. Therefore, inevitably, it can be supposed that the demand of the NTD silicon is considerably increased. However, it is considered likely that the irradiation capacity will not be large enough to meet the increasing demand. After all, the large irradiation capacity for NTD such as a reactor dedicated to the silicon irradiation will be constructed depending on the industrial demand for NTD silicon. In this work, we investigated the relationship between the hybrid electric vehicle (HEV) industry and the NTD silicon production. Also, we surveyed the prospect for the production of the HEV. Then, we deduced the worldwide demand for the NTD silicon associated with the HEV production. This work can be utilized as the basic material for the construction of the new irradiation facility such as NTD-dedicated neutron source

  11. Power Generation Expansion Optimization Model Considering Multi-Scenario Electricity Demand Constraints: A Case Study of Zhejiang Province, China

    Directory of Open Access Journals (Sweden)

    Peng Wang

    2018-06-01

    Full Text Available Reasonable and effective power planning contributes a lot to energy efficiency improvement, as well as the formulation of future economic and energy policies for a region. Since only a few provinces in China have nuclear power plants so far, nuclear power plants were not considered in many provincial-level power planning models. As an extremely important source of power generation in the future, the role of nuclear power plants can never be overlooked. In this paper, a comprehensive and detailed optimization model of provincial-level power generation expansion considering biomass and nuclear power plants is established from the perspective of electricity demand uncertainty. This model has been successfully applied to the case study of Zhejiang Province. The findings suggest that the nuclear power plants will contribute 9.56% of the total installed capacity, and it will become the second stable electricity source. The lowest total discounted cost is 1033.28 billion RMB and the fuel cost accounts for a large part of the total cost (about 69%. Different key performance indicators (KPI differentiate electricity demand in scenarios that are used to test the model. Low electricity demand in the development mode of the comprehensive adjustment scenario (COML produces the optimal power development path, as it provides the lowest discounted cost.

  12. Analysis of PG&E`s residential end-use metered data to improve electricity demand forecasts -- final report

    Energy Technology Data Exchange (ETDEWEB)

    Eto, J.H.; Moezzi, M.M.

    1993-12-01

    This report summarizes findings from a unique project to improve the end-use electricity load shape and peak demand forecasts made by the Pacific Gas and Electric Company (PG&E) and the California Energy Commission (CEC). First, the direct incorporation of end-use metered data into electricity demand forecasting models is a new approach that has only been made possible by recent end-use metering projects. Second, and perhaps more importantly, the joint-sponsorship of this analysis has led to the development of consistent sets of forecasting model inputs. That is, the ability to use a common data base and similar data treatment conventions for some of the forecasting inputs frees forecasters to concentrate on those differences (between their competing forecasts) that stem from real differences of opinion, rather than differences that can be readily resolved with better data. The focus of the analysis is residential space cooling, which represents a large and growing demand in the PG&E service territory. Using five years of end-use metered, central air conditioner data collected by PG&E from over 300 residences, we developed consistent sets of new inputs for both PG&E`s and CEC`s end-use load shape forecasting models. We compared the performance of the new inputs both to the inputs previously used by PG&E and CEC, and to a second set of new inputs developed to take advantage of a recently added modeling option to the forecasting model. The testing criteria included ability to forecast total daily energy use, daily peak demand, and demand at 4 P.M. (the most frequent hour of PG&E`s system peak demand). We also tested the new inputs with the weather data used by PG&E and CEC in preparing their forecasts.

  13. Biomass for electricity in the EU-27: Potential demand, CO2 abatements and breakeven prices for co-firing

    International Nuclear Information System (INIS)

    Bertrand, Vincent; Dequiedt, Benjamin; Le Cadre, Elodie

    2014-01-01

    This paper analyses the potential of biomass-based electricity in the EU-27 countries, and interactions with climate policy and the EU ETS. We estimate the potential biomass demand from the existing power plants, and we match our estimates with the potential biomass supply in Europe. Furthermore, we compute the CO2 abatement associated with the co-firing opportunities in European coal plants. We find that the biomass demand from the power sector may be very high compared with potential supply. We also identify that co-firing can produce high volumes of CO 2 abatements, which may be two times larger than that of the coal-to-gas fuel switching. We also compute biomass and CO2 breakeven prices for co-firing. Results indicate that biomass-based electricity remains profitable with high biomass prices, when the carbon price is high: a Euros 16–24 (25–35, respectively) biomass price (per MWh prim ) for a Euros 20 (50, respectively) carbon price. Hence, the carbon price appears as an important driver, which can make profitable a high share of the potential biomass demand from the power sector, even with high biomass prices. This aims to gain insights on how biomass market may be impacted by the EU ETS and others climate policies. - Highlights: • Technical potential of biomass (demand and CO 2 abatement) in European electricity. • Calculation for co-firing and biomass power plants; comparison with potential biomass supply in EU-27 countries. • Calculation of biomass and CO 2 breakeven prices for co-firing. • Potential demand is 8–148% of potential supply (up to 80% of demand from co-firing). • High potential abatement from co-firing (up to 365 Mt/yr); Profitable co-firing with €16-24 (25–35) biomass price for €20 (50) CO 2 price

  14. Barriers and Opportunities to Broader Adoption of Integrated Demand Side Management at Electric Utilities: A Scoping Study

    Energy Technology Data Exchange (ETDEWEB)

    Potter, Jennifer [Hawaii Natural Energy Institute, Honolulu, HI (United States); Stuart, Elizabeth [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Energy Analysis and Environmental Impacts Div.; Cappers, P [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Energy Analysis and Environmental Impacts Div.

    2018-02-13

    Integrated demand-side management (IDSM) is a strategic approach to designing and delivering a portfolio of demand side management (DSM) programs to customers. IDSM typically delivers customer centric strategies with the goal of increasing the amount of DSM in the field, but doing so in a way that integrates various measures and technologies to improve their collective performance and/or penetration. Specifically, IDSM can be defined as the integrated or coordinated delivery of three or more of: (1) energy efficiency (EE), (2) demand response (DR), (3) distributed generation (DG), (4) storage, (5) electric vehicle (EV) technologies, and (6) time-based rate programs to residential and commercial electric utility customers. The electric industry’s limited experience deploying IDSM to date suggests that significant barriers may exist. A Berkeley Lab report “Barriers and Opportunities to Broader Adoption of Integrated Demand Side Management at Electric Utilities: A Scoping Study” explores recent electric utility experience with IDSM to provide an assessment of the barriers and potential benefits perceived or experienced by program administrators in their attempts to implement integrated programs. The research draws on surveys and interviews with eleven staff from a sample of eight DSM program administrators and program implementers who were currently implementing or had previously attempted to implement an IDSM program or initiative. Respondents provided their perspectives on drivers for IDSM and barriers to broader deployment. They also reported on actions they had undertaken to promote expanded delivery of IDSM and provided their assessments of the most important under-tapped opportunities for expanding IDSM efforts, both for program administrator and regulatory organizations.

  15. Methodology of demand forecast by market analysis of electric power and load curves

    International Nuclear Information System (INIS)

    Barreiro, C.J.; Atmann, J.L.

    1989-01-01

    A methodology for demand forecast of consumer classes and their aggregation is presented. An analysis of the actual attended market can be done by appropriate measures and load curves studies. The suppositions for the future market behaviour by consumer classes (industrial, residential, commercial, others) are shown, and the actions for optimise this market are foreseen, obtained by load curves modulations. The process of future demand determination is obtained by the appropriate aggregation of this segmented demands. (C.G.C.)

  16. Electricity demand and energy consumption in horticulture and conclusions bearing on energy economy. AEL-Bericht

    Energy Technology Data Exchange (ETDEWEB)

    1980-01-01

    The studies demonstrate that horticultural entreprises, esp. those with a higher electricity consumption, have often not settled for a more favourable electricity tariff. Nor do they use cheaper electricity at slack periods (night current) to the extent possible. Substantial improvement could be obtained above all by fully utilizing the installed capacity through purposeful utilization of machinery and interlocking of major consumers. Measures appropriate to this end are listed allowing a possible economic utilization of electric energy.

  17. Modelling of Hot Water Storage Tank for Electric Grid Integration and Demand Response Control

    DEFF Research Database (Denmark)

    Sinha, Rakesh; Bak-Jensen, Birgitte; Pillai, Jayakrishnan Radhakrishna

    2017-01-01

    District heating (DH), based on electric boilers, when integrated into electric network has potential of flexible load with direct/indirect storage to increase the dynamic stability of the grid in terms of power production and consumption with wind and solar. The two different models of electric...

  18. Climate change is projected to have severe impacts on the frequency and intensity of peak electricity demand across the United States.

    Science.gov (United States)

    Auffhammer, Maximilian; Baylis, Patrick; Hausman, Catherine H

    2017-02-21

    It has been suggested that climate change impacts on the electric sector will account for the majority of global economic damages by the end of the current century and beyond [Rose S, et al. (2014) Understanding the Social Cost of Carbon: A Technical Assessment ]. The empirical literature has shown significant increases in climate-driven impacts on overall consumption, yet has not focused on the cost implications of the increased intensity and frequency of extreme events driving peak demand, which is the highest load observed in a period. We use comprehensive, high-frequency data at the level of load balancing authorities to parameterize the relationship between average or peak electricity demand and temperature for a major economy. Using statistical models, we analyze multiyear data from 166 load balancing authorities in the United States. We couple the estimated temperature response functions for total daily consumption and daily peak load with 18 downscaled global climate models (GCMs) to simulate climate change-driven impacts on both outcomes. We show moderate and heterogeneous changes in consumption, with an average increase of 2.8% by end of century. The results of our peak load simulations, however, suggest significant increases in the intensity and frequency of peak events throughout the United States, assuming today's technology and electricity market fundamentals. As the electricity grid is built to endure maximum load, our findings have significant implications for the construction of costly peak generating capacity, suggesting additional peak capacity costs of up to 180 billion dollars by the end of the century under business-as-usual.

  19. Analysis on the Electric Power Supply - Demand Measures of Japan in 2011 Summer after Earthquake and Tsunami

    International Nuclear Information System (INIS)

    Lee, Y. E.; Chang, H. S.

    2011-01-01

    Only 12 of 54 nuclear reactors are in operation as of September 1, 2011 in the wake of the earthquake and tsunami in Japan. The share of nuclear power in the nation's installation capacity fell to about 14% in August from about 30% before March 11, 2011. Government or many of research institutes estimated that the power supply system in Japan would fall to the minus reserve margin, if the nuclear power stations could not be restarted as scheduled. However, the current situation of power supply system in Japan is less severe than expected before, because the power companies and public have engaged in various diligent efforts to boost supply capacity or reduce demand in response to the electric power crisis. This paper aims to analyze the how much Japan electric power supply system depends on the nuclear power, what kinds of countermeasures of electric power supply-demand are taken by electricity companies in summer time to avoid the blackouts and why the saving electricity in Japan could be possible unlike Korea. Insights from this paper would be taken into account in the long term energy planning, even though the further study in depth should be followed

  20. The impact of ICT investment and energy price on industrial electricity demand: Dynamic growth model approach

    Energy Technology Data Exchange (ETDEWEB)

    Cho, Youngsang; Lee, Jongsu; Kim, Tai-Yoo [Technology Management, Economics and Policy Program, College of Engineering, Seoul National University, Shillim-Dong San56-1, Gwanak-Ku, Seoul 151-742 (Korea)

    2007-09-15

    The authors investigate the effects of information and communications technology (ICT) investment, electricity price, and oil price on the consumption of electricity in South Korea's industries using a logistic growth model. The concept electricity intensity is used to explain electricity consumption patterns. An empirical analysis implies that ICT investment in manufacturing industries that normally consume relatively large amounts of electricity promotes input factor substitution away from the labor intensive to the electricity intensive. Moreover, results also suggest that ICT investment in some specific manufacturing sectors is conducive to the reduction of electricity consumption, whereas ICT investment in the service sector and most manufacturing sectors increases electricity consumption. It is concluded that electricity prices critically affect electricity consumption in half of South Korea's industrial sectors, but not in the other half, a finding that differs somewhat from previous research results. Reasons are suggested to explain why the South Korean case is so different. Policymakers may find this study useful, as it answers the question of whether ICT investment can ultimately reduce energy consumption and may aid in planning the capacity of South Korea's national electric power. (author)

  1. The impact of ICT investment and energy price on industrial electricity demand: Dynamic growth model approach

    International Nuclear Information System (INIS)

    Cho, Youngsang; Lee, Jongsu; Kim, Tai-Yoo

    2007-01-01

    The authors investigate the effects of information and communications technology (ICT) investment, electricity price, and oil price on the consumption of electricity in South Korea's industries using a logistic growth model. The concept electricity intensity is used to explain electricity consumption patterns. An empirical analysis implies that ICT investment in manufacturing industries that normally consume relatively large amounts of electricity promotes input factor substitution away from the labor intensive to the electricity intensive. Moreover, results also suggest that ICT investment in some specific manufacturing sectors is conducive to the reduction of electricity consumption, whereas ICT investment in the service sector and most manufacturing sectors increases electricity consumption. It is concluded that electricity prices critically affect electricity consumption in half of South Korea's industrial sectors, but not in the other half, a finding that differs somewhat from previous research results. Reasons are suggested to explain why the South Korean case is so different. Policymakers may find this study useful, as it answers the question of whether ICT investment can ultimately reduce energy consumption and may aid in planning the capacity of South Korea's national electric power. (author)

  2. Operations of electric taxis to serve advance reservations by trip chaining: Sensitivity analysis on network size, customer demand and number of charging stations

    Directory of Open Access Journals (Sweden)

    Hao Wang

    2016-10-01

    Full Text Available This research investigated the performance of an Electric Taxi (ET fleet that catered solely for customers with advance reservations. In a previously related research, a customized Paired Pickup and Delivery Problem with Time Window and Charging Station (PPDPTWCS had been formulated to solve for the minimum number of taxis that would serve a fixed set of customer demand. The concept behind this fleet optimization was to chain multiple customer trips and trips to Charging Stations (CSs to form a route and assigned to a taxi driver. In this paper the sensitivity of the ET fleet’s operations with respect to network sizes, customer demand densities and number of CSs have been investigated. It also analyzed the market shares of the CSs and the occupancy of a CS over time. The results showed that, (1 the expansion of network size or the increase in customer demand density led to increase in fleet size, number of trips to the CSs and maximum occupancies at the CSs but these performance measures grew at different rates; (2 when the network size and number of CSs were fixed, an increase in customer demand density led to a better utilization of taxis in terms of more customers served per taxi and higher average revenue per taxi; (3 given the same network size and demand density, the ET fleet’s performance was relatively insensitive to the number of CSs; and (4 the usage of individual CS was affected by the number of CS and their locations; and (5 when all the ETs were fully charged at the beginning of the same shift hour, they visited the CSs in bunches when their batteries were about to run out. These findings contribute to a better understanding of the operations of the ET fleet and the CSs. They could be used for making better decisions in the planning of ET operations.

  3. Machine learning for identifying demand patterns of home energy management systems with dynamic electricity pricing

    NARCIS (Netherlands)

    Koolen, D. (Derck); Sadat-Razavi, N. (Navid); W. Ketter (Wolfgang)

    2017-01-01

    textabstractEnergy management plays a crucial role in providing necessary system flexibility to deal with the ongoing integration of volatile and intermittent energy sources. Demand Response (DR) programs enhance demand flexibility by communicating energy market price volatility to the end-consumer.

  4. Local muscle metabolic demand induced by neuromuscular electrical stimulation and voluntary contractions at different force levels: a NIRS study

    Directory of Open Access Journals (Sweden)

    Makii Muthalib

    2016-06-01

    Full Text Available Functional Muscle metabolic demand during contractions evoked by neuromuscular electrical stimulation (NMES has been consistently documented to be greater than voluntary contractions (VOL at the same force level (10-50% maximal voluntary contraction-MVC. However, we have shown using a near-infrared spectroscopy (NIRS technique that local muscle metabolic demand is similar between NMES and VOL performed at MVC levels, thus controversy exists. This study therefore compared biceps brachii muscle metabolic demand (tissue oxygenation index-TOI and total hemoglobin volume-tHb during a 10s isometric contraction of the elbow flexors between NMES (stimulation frequency of 30Hz and current level to evoke 30% MVC and VOL at 30% MVC (VOL-30%MVC and MVC (VOL-MVC level in 8 healthy men (23-33-y. Greater changes in TOI and tHb induced by NMES than VOL-30%MVC confirm previous studies of a greater local metabolic demand for NMES than VOL at the same force level. The same TOI and tHb changes for NMES and VOL-MVC suggest that local muscle metabolic demand and intramuscular pressure were similar between conditions. In conclusion, these findings indicate that NMES induce a similar local muscle metabolic demand as that of maximal VOL.

  5. Local Muscle Metabolic Demand Induced by Neuromuscular Electrical Stimulation and Voluntary Contractions at Different Force Levels: A NIRS Study.

    Science.gov (United States)

    Muthalib, Makii; Kerr, Graham; Nosaka, Kazunori; Perrey, Stephane

    2016-06-13

    Functional Muscle metabolic demand during contractions evoked by neuromuscular electrical stimulation (NMES) has been consistently documented to be greater than voluntary contractions (VOL) at the same force level (10-50% maximal voluntary contraction-MVC). However, we have shown using a near-infrared spectroscopy (NIRS) technique that local muscle metabolic demand is similar between NMES and VOL performed at MVC levels, thus controversy exists. This study therefore compared biceps brachii muscle metabolic demand (tissue oxygenation index-TOI and total hemoglobin volume-tHb) during a 10s isometric contraction of the elbow flexors between NMES (stimulation frequency of 30Hz and current level to evoke 30% MVC) and VOL at 30% MVC (VOL-30%MVC) and MVC (VOL-MVC) level in 8 healthy men (23-33-y). Greater changes in TOI and tHb induced by NMES than VOL-30%MVC confirm previous studies of a greater local metabolic demand for NMES than VOL at the same force level. The same TOI and tHb changes for NMES and VOL-MVC suggest that local muscle metabolic demand and intramuscular pressure were similar between conditions. In conclusion, these findings indicate that NMES induce a similar local muscle metabolic demand as that of maximal VOL.

  6. Forecasting the Electricity Demand and Market Shares in Retail Electricity Market Based on System Dynamics and Markov Chain

    OpenAIRE

    Qingyou Yan; Chao Qin; Mingjian Nie; Le Yang

    2018-01-01

    Due to the deregulation of retail electricity market, consumers can choose retail electric suppliers freely, and market entities are facing fierce competition because of the increasing number of new entrants. Under these circumstances, forecasting the changes in all market entities, when market share stabilized, is important for suppliers making marketing decisions. In this paper, a market share forecasting model was established based on Markov chain, and a system dynamics model was construct...

  7. Comparison of particle swarm optimization and other metaheuristics on electricity demand estimation: A case study of Iran

    International Nuclear Information System (INIS)

    Askarzadeh, Alireza

    2014-01-01

    The importance of energy demand estimation stems from energy planning, formulating strategies and recommending energy policies. Most often, energy demand is mathematically formulated by socio-economic indicators. The challenging problem is to determine the optimal or near optimal weighting factors. Inspired by social behavior of bird flocking or fish schooling, PSO (particle swarm optimization) is a population-based search technique which has attracted significant attention to tackle the complexity of difficult optimization problems. This paper studies the performance of different PSO variants for estimating Iran's electricity demand. Seven PSO variants namely, original PSO, PSO-w (PSO with weighting factor), PSO-cf (PSO with constriction factor), PSO-rf (PSO with repulsion factor), PSO-vc (PSO with velocity control), CLPSO (comprehensive learning PSO) and a MPSO (modified PSO), are used to find the unknown weighting factors based on the data from 1982 to 2003. The validation process is then conducted by testing the optimized models by using the data from 2004 to 2009. It is seen that PSO-vc produces more promising results than the other variants, HS (harmony search) and ABSO (artificial bee swarm optimization) algorithms in terms of MAPE (mean absolute percentage error). This value is obtained 2.47 and 2.50 for the exponential and quadratic models, respectively. - Highlights: • Electricity demand estimation is modelled using socio-economic indicators. • Different PSO variants are investigated in terms of accuracy. • Exponential model can estimate the Iran's electricity demand with high accuracy. • PSO with velocity control produces more accurate result than the others

  8. Incentive-based demand response programs designed by asset-light retail electricity providers for the day-ahead market

    DEFF Research Database (Denmark)

    Fotouhi Ghazvini, Mohammad Ali; Faria, Pedro; Ramos, Sergio

    2015-01-01

    how a REP with light physical assets, such as DG (distributed generation) units and ESS (energy storage systems), can survive in a competitive retail market. The paper discusses the effective risk management strategies for the REPs to deal with the uncertainties of the DAM (day-ahead market) and how...... to hedge the financial losses in the market. A two-stage stochastic programming problem is formulated. It aims to establish the financial incentive-based DR programs and the optimal dispatch of the DG units and ESSs. The uncertainty of the forecasted day-ahead load demand and electricity price is also...... taken into account with a scenario-based approach. The principal advantage of this model for REPs is reducing the risk of financial losses in DAMs, and the main benefit for the whole system is market power mitigation by virtually increasing the price elasticity of demand and reducing the peak demand....

  9. Outline of energy (electricity) supply and demand outlook in Asian APEC countries

    International Nuclear Information System (INIS)

    Fujime, Kazuya

    1995-01-01

    Oil: Japan's oil demand is projected to be on a gradual decline in the future due to implementation of policy measures aimed at achieving that objective, while consumption of oil in three areas - China, NIES and six ASEAN countries -- is projected to increase to reach a level nearly three times as large as Japan's demand by 2010. Supply of oil in the region is projected to level off, making it necessary for the region to increase its reliance on other areas for additional volumes of oil supply. Coal: Demand for coal is projected to grow against a background of expansion of coal-fired power generation. Coal demand in China, in particular, is projected to grow to such an extent that China may become a net coal importer, thus having a great impact on coal supply and demand in Asian countries. Natural gas: Demand for natural gas is projected to grow in the region, centering on NIES and ASEAN countries. Although production in ASEAN countries is expected to increase, the region is anticipated to increase its reliance on other areas for natural gas supply from medium - and long term perspectives. Oil products: Demand for oil products is projected to grow due to stepped-up industrialization and motorization in China, NIES and ASEAN countries. From medium - and long-term perspectives, considerable volumes of additional oil product supply will become necessary, unless large-scale refineries are newly built or expanded within the region centering on China. (author)

  10. Analysis of the electricity demand of Greece for optimal planning of a large-scale hybrid renewable energy system

    Science.gov (United States)

    Tyralis, Hristos; Karakatsanis, Georgios; Tzouka, Katerina; Mamassis, Nikos

    2015-04-01

    The Greek electricity system is examined for the period 2002-2014. The demand load data are analysed at various time scales (hourly, daily, seasonal and annual) and they are related to the mean daily temperature and the gross domestic product (GDP) of Greece for the same time period. The prediction of energy demand, a product of the Greek Independent Power Transmission Operator, is also compared with the demand load. Interesting results about the change of the electricity demand scheme after the year 2010 are derived. This change is related to the decrease of the GDP, during the period 2010-2014. The results of the analysis will be used in the development of an energy forecasting system which will be a part of a framework for optimal planning of a large-scale hybrid renewable energy system in which hydropower plays the dominant role. Acknowledgement: This research was funded by the Greek General Secretariat for Research and Technology through the research project Combined REnewable Systems for Sustainable ENergy DevelOpment (CRESSENDO; grant number 5145)

  11. An assessment of the potential contribution from waste-to-energy facilities to electricity demand in Saudi Arabia

    International Nuclear Information System (INIS)

    Ouda, Omar K.M.; Cekirge, Huseyin M.; Raza, Syed A.R.

    2013-01-01

    Highlights: • This research evaluates the potential contribution of WTE to Saudi power demand. • Two scenarios were developed: Mass Burn and Mass Burn with recycling to year 2032. • Mass Burn will generate 2073 Megawatts (MW) about 1.73% of 2032 peak power demand. • Mass Burn with recycling will generate 166 MW about 0.14% of 2032 peak power demand. - Abstract: The Kingdom of Saudi Arabia (KSA) is the largest crude oil producer in the world and possesses the largest oil reserves. The crude oil revenue has resulted in a massive socio-economic development over the last four decades. This situation has resulted in rapid growth of the country’s electricity demand and municipal solid waste (MSW) generation. The KSA is proposing an impressive plan towards renewable energy utilization that includes waste-to-energy (WTE) facilities. This research assesses the potential contribution of WTE facilities to total Saudi peak power demand up to the year 2032 based on two scenarios: Mass Burn and Mass Burn with recycling for the entire country and for six major cities in the KSA. The analysis shows a potential to produce about 2073 Megawatts (MW) based on a Mass Burn scenario and about 166 MW based on Mass Burn with recycling scenario. These values amount to about 1.73% and 0.14% of the projected 2032 peak electricity demand of 120 Gigawatt. The forecasted results of each city from the two scenarios can be used to design future WTE facilities in the main cities of Saudi Arabia. Further investigations are recommended to evaluate the two scenarios based on financial, social, technical, and environmental criteria

  12. How to fit demand side management (DSM) into current Chinese electricity system reform?

    International Nuclear Information System (INIS)

    Yu Yongzhen

    2012-01-01

    DSM is one of the best and most practical policy tools available to China for balancing environmental protection and economic growth. The new round of electricity system reform provides a good opportunity to consolidate and integrate DSM policy and expedite its development and implementation. DSM policy can be upgraded by incorporating it into the current electricity system reform. Comparing the potential acceleration of electricity price reform with the possibility of imposing a System Benefit Charge (SBC), the author argues that support for a SBC would be much easier to gather among policymakers and stakeholders in a short time and would have a much better policy effect in the current situation. The author discusses three kinds of price discrimination related to the DSM development in China: time-based electricity pricing, electricity price discrimination for industrial structure adjustment in China (Fujian Province as a case), and direct power purchases by large customers and preferential tariff policy. These can be well designed to be combined with DSM and energy efficiency policy. - Highlights: ► Elements of DSM have been in place since 1993, but without even and reinforced policy. ► DSM can be upgraded by fitting it into current Chinese electricity system reform. ► Both electricity price reform and SBC would mean increases in electricity payment. ►Imposing SBC is much easier and better than speeding up electricity price reform. ► Three kinds of price discrimination can be well designed to be combined with DSM.

  13. Including Energy Efficiency and Renewable Energy Policies in Electricity Demand Projections

    Science.gov (United States)

    Find more information on how state and local air agencies can identify on-the-books EE/RE policies, develop a methodology for projecting a jurisdiction's energy demand, and estimate the change in power sector emissions.

  14. Co-optimization of Energy and Demand-Side Reserves in Day-Ahead Electricity Markets

    Science.gov (United States)

    Surender Reddy, S.; Abhyankar, A. R.; Bijwe, P. R.

    2015-04-01

    This paper presents a new multi-objective day-ahead market clearing (DAMC) mechanism with demand-side reserves/demand response (DR) offers, considering realistic voltage-dependent load modeling. The paper proposes objectives such as social welfare maximization (SWM) including demand-side reserves, and load served error (LSE) minimization. In this paper, energy and demand-side reserves are cleared simultaneously through co-optimization process. The paper clearly brings out the unsuitability of conventional SWM for DAMC in the presence of voltage-dependent loads, due to reduction of load served (LS). Under such circumstances multi-objective DAMC with DR offers is essential. Multi-objective Strength Pareto Evolutionary Algorithm 2+ (SPEA 2+) has been used to solve the optimization problem. The effectiveness of the proposed scheme is confirmed with results obtained from IEEE 30 bus system.

  15. An Economic Customer-Oriented Demand Response Model in Electricity Markets

    DEFF Research Database (Denmark)

    Sharifi, Reza; Anvari-Moghaddam, Amjad; Fathi, S. Hamid

    2018-01-01

    Consumer choice theory is a branch of microeconomics. This theory relates to adjusting consumption expenditures and consumer demand curve. Consumer choice science is trying to realize the buyer's decision-making process. This science studies customer characteristics, such as behavioral criteria......, to understand the consumer’s need. The concept of price elasticity of demand (PED) has also been derived from this theory. In fact, the PED is the percentage of changes in the amount of demand relative to the price changes. In consumer choice theory, for each consumer according to behavioral criteria, a unique...... demand response (DR) models have been developed based on this concept, this will also be deemed as a disadvantage for them. In this paper, we propose an economic DR model based on economic theories and mathematical methods. In addition to abate the defects of price-elasticity based DR models...

  16. Modelling energy demand for a fleet of hydrogen-electric vehicles interacting with a clean energy hub

    International Nuclear Information System (INIS)

    Syed, F.; Fowler, M.; Wan, D.; Maniyali, Y.

    2009-01-01

    This paper details the development of an energy demand model for a hydrogen-electric vehicle fleet and the modelling of the fleet interactions with a clean energy hub. The approach taken is to model the architecture and daily operation of every individual vehicle in the fleet. A generic architecture was developed based on understanding gained from existing detailed models used in vehicle powertrain design, with daily operation divided into two periods: charging and travelling. During the charging period, the vehicle charges its Electricity Storage System (ESS) and refills its Hydrogen Storage System (HSS), and during the travelling period, the vehicle depletes the ESS and HSS based on distance travelled. Daily travel distance is generated by a stochastic model and is considered an input to the fleet model. The modelling of a clean energy hub is also presented. The clean energy hub functions as an interface between electricity supply and the energy demand (i.e. hydrogen and electricity) of the vehicle fleet. Finally, a sample case is presented to demonstrate the use of the fleet model and its implications on clean energy hub sizing. (author)

  17. Impact of electricity prices and volumetric water allocation on energy and groundwater demand management: analysis from Western India

    International Nuclear Information System (INIS)

    Kumar, M.D.

    2005-01-01

    In recent years, power tariff policy has been increasingly advocated as a mean to influence groundwater use and withdrawal decisions of farmers in view of the failure of existing direct and indirect regulations on groundwater withdrawal in India. Many researchers argue that pro rata electricity tariff, with built in positive marginal cost of pumping could bring about efficient use of the resource, though some argue that the levels of tariff in which demand becomes elastic to pricing are too high to be viable from political and socio-economic points of view. The paper presents a theoretical model to analyze farmers' response to changes in power tariff and water allocation regimes vis a vis energy and groundwater use. It validates the model by analyzing water productivity in groundwater irrigation under different electricity pricing structures and water allocation regimes. Water productivity was estimated using primary data of gross crop inputs, cost of all inputs, and volumetric water inputs. The analysis shows that unit pricing of electricity influences groundwater use efficiency and productivity positively. It also shows that the levels of pricing at which demand for electricity and groundwater becomes elastic to tarif